U.S. patent application number 16/219203 was filed with the patent office on 2019-04-18 for method of predicting personalized response to cancer treatment with immune checkpoint inhibitors, method of treating cancer, and kit therefor.
This patent application is currently assigned to Rappaport Family Institute for Research in the Medical Sciences. The applicant listed for this patent is Rappaport Family Institute for Research in the Medical Sciences. Invention is credited to Yuval Shaked.
Application Number | 20190113513 16/219203 |
Document ID | / |
Family ID | 64566193 |
Filed Date | 2019-04-18 |
United States Patent
Application |
20190113513 |
Kind Code |
A1 |
Shaked; Yuval |
April 18, 2019 |
Method of Predicting Personalized Response to Cancer Treatment with
Immune Checkpoint Inhibitors, Method of Treating Cancer, and Kit
Therefor
Abstract
A method and a kit are provided for predicting a favorable or a
non-favorable response of a cancer patient to treatment with an
immune checkpoint inhibitor by determining in a biological sample
obtained from the cancer patient, before and after the treatment,
the changes of the levels of factors/biomarkers generated by the
cancer patient in response to said treatment, and a method for
treatment of a cancer patient with an immune checkpoint
inhibitor.
Inventors: |
Shaked; Yuval; (Binyamina,
IL) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Rappaport Family Institute for Research in the Medical
Sciences |
Haifa |
|
IL |
|
|
Assignee: |
Rappaport Family Institute for
Research in the Medical Sciences
Haifa
IL
|
Family ID: |
64566193 |
Appl. No.: |
16/219203 |
Filed: |
December 13, 2018 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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PCT/IL2018/050609 |
Jun 4, 2018 |
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16219203 |
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62594141 |
Dec 4, 2017 |
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62564392 |
Sep 28, 2017 |
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62514851 |
Jun 4, 2017 |
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Current U.S.
Class: |
1/1 |
Current CPC
Class: |
G01N 33/6857 20130101;
C07K 16/2818 20130101; C07K 16/248 20130101; G16B 5/00 20190201;
G16H 50/30 20180101; A61P 35/00 20180101; C07K 16/2878 20130101;
G01N 33/74 20130101; G01N 33/577 20130101; G01N 33/57484 20130101;
C07K 16/2803 20130101; G01N 33/574 20130101; A61K 2039/505
20130101; G01N 2800/52 20130101; G16H 50/20 20180101; G16B 25/10
20190201; G06F 17/15 20130101 |
International
Class: |
G01N 33/574 20060101
G01N033/574; A61P 35/00 20060101 A61P035/00; G16H 50/20 20060101
G16H050/20; C07K 16/28 20060101 C07K016/28; G16B 25/10 20060101
G16B025/10; G16B 5/00 20060101 G16B005/00 |
Claims
1. A method for predicting the response of a cancer patient to
treatment with an immune checkpoint inhibitor (ICI), the method
comprising the steps of: (i) performing an assay on a biological
sample selected from blood plasma, whole blood, blood serum or
peripheral blood mononuclear cells obtained from the cancer patient
at a time period after a session of treatment with said ICI, to
determine the levels of one or more of a plurality of factors
induced in the circulation of said cancer patient in response to
treatment with said ICI, said one or more of the plurality of
factors promoting responsiveness or non-responsiveness of the
cancer patient to the treatment with said ICI; (ii) obtaining
reference levels for each of the one or more of the plurality of
the induced factors of step (i) in a biological sample obtained
from the cancer patient before said session of treatment with the
ICI; (iii) establishing the fold change for each of the one or more
of the plurality of the induced factors of step (i) by comparing
the level of each induced factor of step (i) with the reference
level of step (ii) for the same factor; and (iv) determining that
the cancer patient has a favorable or a non-favorable response to
the treatment with said ICI based on the fold change established in
step (iii) for one or more of the plurality of induced factors of
step (i).
2. The method of claim 1, wherein the biological sample of steps
(i) and (ii) is blood plasma.
3. The method of claim 1, wherein said session of treatment with
the ICI is the first session of treatment with said ICI, the
biological sample of step (i) is obtained from the cancer patient
at about 20, 24, 30, 36, 40, 48, 50, 60, 72 hours or more,
including up to one week or more, up to three weeks or more, after
said first session of treatment, and the reference biological
sample of step (ii) is obtained from the cancer patient at a time
point including at about 72 hours or less, including at about 60,
50, 48, 40, 36, 30, 24 or 20 hours or less or just before said
first session of treatment with the ICI.
4. The method of claim 1, wherein said session of treatment with
the ICI is one of multiple sessions of treatment that is not the
first session of treatment with the ICI, and the biological sample
is obtained from the cancer patient at any time point between two
consecutive sessions of treatment with the ICI, wherein said
biological sample is simultaneously the biological sample of step
(i) and the reference biological sample according to step (ii) for
the next session assay according to step (i).
5. The method of claim 4, wherein the time between two consecutive
sessions of treatment may be of 2 or 3 weeks, depending on the ICI,
and the biological sample may be obtained at day 1, 2, 3, 7, 14, or
21 days after the session of treatment that is not the first
session of treatment with the ICI.
6. The method of claim 1, wherein the fold-change established in
step (iii) is defined by a fold change of .gtoreq.1.5 indicating
upregulation or a fold change of .ltoreq.0.5 indicating
down-regulation in the level of each of the one or more of the
plurality of factors induced in the circulation of the cancer
patient in response to the treatment with the ICI, these values
being considered significant and predictive of a non-favorable or
favorable response of the cancer patient to the treatment with the
said ICI.
7. The method of claim 6, wherein the prediction of a favorable or
a non-favorable response of the cancer patient to the treatment
with the ICI is based on significant fold changes of one or more,
optionally two or more, three or more, four or more, five or more,
six or more, seven or more, eight or more, nine or more, ten or
more, eleven or more, twelve or more, thirteen or more, fourteen or
more, fifteen or more, twenty or more, or twenty-five or more, of
the induced factors.
8. The method of claim 1, wherein the factors induced in the
circulation of said cancer patient in response to treatment with
said ICI are molecular factors including cytokines, chemokines,
growth factors, enzymes and soluble receptors.
9. The method of claim 8, wherein the factors are pro-tumorigenic
or pro-metastatic factors, and the pro-tumorigenic factors may be
pro-angiogenic, pro-inflammatory/chemotactic or proliferative
growth factors.
10. The method of claim 9, wherein if there is an increase
(up-regulation) of at least about 1.5-fold in the level of one or
more of the pro-tumorigenic or pro-metastatic factors, then the
prediction is of a non-favorable response of the cancer patient to
the treatment with the ICI, and if there is a decrease
(down-regulation) of at least about 0.5-fold in the level of one or
more of the pro-tumorigenic or pro-metastatic factors, then the
prediction is of a favorable response of the cancer patient to the
treatment with the ICI.
11. The method of claim 1, wherein the ICI is an inhibitor to an
immune checkpoint selected from PD-1, PD-L1, CTLA-4, A2AR, BT-H3,
BT-H4, BT-H5; BTLA; IDO; KIR; LAG-3; TDO; TIM-3; or VISTA.
12. The method of claim 11, wherein the ICI is a monoclonal
antibody selected from an anti-PD-1, an anti-PD-L1, or an
anti-CTLA-4.
13. The method of claim 12, wherein the anti-PD-1 monoclonal
antibody is Pembrolizumab, Nivolumab, Pidilizumab, Cemiplimab,
AMP-224, MEDI0680, or Spartalizumab.
14. The method of claim 12, wherein the anti-PD-L1 monoclonal
antibody is Atezolizumab, Avelumab, Durvalumab or MDX-1105.
15. The method of claim 12, wherein the anti-CTLA-4 monoclonal
antibody is Ipilimumab or Tremelimumab.
16. The method of claim 11, wherein the anti-LAG-3 monoclonal
antibody is Relatlimab, LAG525 or REGN3767; the anti-TIM-3
monoclonal antibody is TSR022 or MBG453; the anti-VISTA monoclonal
antibody is JNJ 61610588; and the anti-MR monoclonal antibody is
Lirilumab.
17. The method of claim 1, wherein the cancer patient is treated
with a combination of two ICIs.
18. The method of claim 17, wherein said combination of two ICIs is
selected from: (i) Nivolumab (anti-PD-1) and Ipilimumab
(anti-CTLA-4); (ii) Nivolumab (anti-PD-1) and Atezolimumab
(anti-PD-L1); Durvalumab (anti-PD-L1) and Tremelimumab
(anti-CTLA-4); Pembrolizumab (anti-PD-1) and Epacadostat (IDO
inhibitor); Nivolumab (anti-PD-1) and Epacadostat (IDO
inhibitor).
19. The method of claim 1, wherein the ICI is in combination with
an agonistic monoclonal antibody against T-cell co-stimulatory
molecules including an anti-ICOS monoclonal antibody such as
MEDI-570 or BMS-986226; an anti-OX40 monoclonal antibody such as
MOXR0916, KHK4083, MEDI0562 or MEDI6469; an anti-CD40 monoclonal
antibody; and an anti-CD137 (4-IBB) such as Urelumab or
Utomilumab.
20. The method of claim 19, wherein the ICI is Nivolumab
(anti-PD-1) and the agonistic monoclonal antibody is Urelumab
(anti-4-IBB).
21. The method of claim 1, wherein the ICI is administered in
combination with one or more conventional cancer therapy including
chemotherapy, targeted cancer therapy and radiotherapy.
22. The method of claim 8, wherein the factors induced by treatment
with the ICI include: ADAMTS1; amphiregulin; Axl; CCL5/RANTES;
CCL17/TARC; EGF; Eotaxin-2; FGF-21; Gas6; G-CSF; GM-CSF; HGF;
IFN-gamma; IL-1Ralpha; IL-2; IL-6; IL-7; IL-10; IL-12p40; IL-13;
IL-33; I-TAC; MadCAM-1; MCP-5; TACI; M-CSF; MMP-9; PDGF-BB;
pro-MMP9; SCF.
23. The method of claim 22, wherein the factors upregulated in
response to anti-PD-1 treatment are selected from: (i)
pro-angiogenic factors including G-CSF, GM-CSF, and PDGF-BB; (ii)
pro-inflammatory and/or chemotactic factors including CCL17/TARC,
CCL5/RANTES, G-CSF, GM-CSF, IFN-gamma, IL-1Ralpha, IL-2, IL-6,
IL-7, IL-10, IL-12p40, IL-13, IL-33 and M-CSF; (iii) proliferative
growth factors including FGF-21, Gas6, and HGF; and (iv) the
pro-metastatic factor MMP-9.
24. The method of claim 22, wherein the factors upregulated in
response to anti-PD-L1 treatment are selected from: (i)
pro-angiogenic factors including G-CSF and SCF; (ii)
pro-inflammatory and/or chemotactic factors including Eotaxin-2,
G-CSF, IL-1ra, IL-6, IL-7, IL-33, I-TAC, MadCAM-1, MCP-5, SCF, and
TACI; (iii) proliferative growth factors including amphiregulin,
Axl, EGF, and HGF; and (iv) pro-metastatic factors including
ADAMTS1 and pro-MMP9.
25. A kit comprising a plurality of antibodies, at least part of
the antibodies of the plurality of antibodies each selectively
binds to each of a plurality of factors that promote responsiveness
or non-responsiveness of a cancer patient to treatment with an
immune checkpoint inhibitor, and instructions for use.
26. The kit of claim 25, wherein said kit is a sandwich or
enzyme-linked immunosorbent assay (ELISA) kit.
27. The kit of claim 25, comprising a plurality of human monoclonal
antibodies, at least part of them each binding specifically to a
pro-tumorigenic factor having pro-angiogenic,
pro-inflammatory/chemotactic or proliferative activity, or to a
pro-metastatic factor, at least some of these pro-tumorigenic and
pro-metastatic factors being predictive of a favorable or a
non-favorable response of a cancer patient to treatment with an
immune checkpoint inhibitor.
28. The kit of claim 27, wherein at least 30 of said monoclonal
antibodies each specifically binds to a factor selected from the
following 30 factors: ADAMTS1, amphiregulin; Axl; CCL5/RANTES;
CCL17/TARC; EGF; Eotaxin-2; FGF-21; Gas6; G-CSF; GM-CSF; HGF;
IFN-gamma; IL-1Ralpha; IL-2; IL-6; IL-7; IL-10; IL-12p40; IL-13;
IL-33; I-TAC; MadCAM-1; MCP-5; TACI; M-CSF; MMP-9; PDGF-BB;
pro-MMP9; and SCF.
29. A method of treating a cancer patient with an immune checkpoint
inhibitor (ICI), the method comprising the steps of: (i) performing
an assay on a biological sample selected from blood plasma, whole
blood, blood serum or peripheral blood mononuclear cells obtained
from the cancer patient at a time period after a session of
treatment with said ICI, to determine the levels of one or more of
a plurality of factors induced in the circulation of said cancer
patient in response to treatment with said ICI, said one or more of
the plurality of factors promoting responsiveness or
non-responsiveness of the cancer patient to the treatment with said
ICI; (ii) obtaining reference levels for each of the one or more of
the plurality of the induced factors of step (i) in a biological
sample selected from blood plasma, whole blood, blood serum or
peripheral blood mononuclear cells, obtained from the cancer
patient before said session of treatment with the ICI; (iii)
establishing the fold change for each of the one or more of the
plurality of the induced factors of step (i) by comparing the level
of each induced factor of step (i) with the reference level of step
(ii) for the same factor; (iv) determining that the cancer patient
has a favorable or a non-favorable response to the treatment with
said ICI based on the fold change established in step (iii) for one
or more of the plurality of induced factors of step (i); and (iva)
if the cancer patient has a non-favorable response to the treatment
with said cancer therapy based on the fold change established in
(iii) for one or more of the plurality of the induced factors, then
selecting a dominant factor among the one or more factors showing a
fold change indicative of said non-favorable response, and treating
the patient with the ICI in combination with an agent that blocks
the dominant factor; or (ivb) if the cancer patient has a favorable
response to the treatment with said ICI based on the fold change of
the level of the one or more factors established in (iii), then
continuing the treatment of the cancer patient with the same
ICI.
30. The method of claim 29, wherein the biological samples of step
(i) and step (ii) are both blood plasma.
31. The method of claim 29, wherein said session of treatment with
the ICI is the first session of treatment with said ICI, the
biological sample of step (i) is obtained from the cancer patient
at about 20, 24, 30, 36, 40, 48, 50, 60, 72 hours or more,
including up to one week or more or up to three weeks or more,
after said first session of treatment, and the reference biological
sample of step (ii) is obtained from the cancer patient at a time
point including at about 72 hours or less, including at about 60,
50, 48, 40, 36, 30, 24 or 20 hours or less or just before said
first session of treatment with the ICI.
32. The method of claim 29, wherein said session of treatment with
the ICI is one of multiple sessions of treatment that is not the
first session of treatment with the ICI, and the biological sample
is obtained from the cancer patient at any time point between two
consecutive sessions of treatment, wherein said biological sample
is simultaneously the biological sample of step (i) and the
reference biological sample according to step (ii) for the next
session assay according to step (i).
33. The method of claim 32, wherein the time between two
consecutive sessions of treatment may be of 2 or 3 weeks, depending
on the ICI, and the biological sample may be obtained at day 1, 2,
3, 7, 14, or 21 days after the session of treatment that is not the
first session of treatment with the ICI.
34. The method of claim 29, wherein the fold-change established in
step (iii) is defined by a fold change of .gtoreq.1.5 indicating
upregulation or a fold change of .ltoreq.0.5 indicating
down-regulation in the level of each of the one or more of the
plurality of factors induced in the circulation of the cancer
patient in response to the treatment with the ICI, these values
being considered significant and predictive of a non-favorable or a
favorable response of the cancer patient to the treatment with said
ICI.
35. The method of claim 34, wherein the prediction of a favorable
or a non-favorable response of the cancer patient to the treatment
with the ICI is based on significant fold changes of one or more,
optionally two or more, three or more, four or more, five or more,
six or more, seven or more, eight or more, nine or more, ten or
more, eleven or more, twelve or more, thirteen or more, fourteen or
more, fifteen or more, twenty or more, or twenty-five or more, of
the induced factors.
36. The method of claim 29, wherein the factors induced in the
circulation of said cancer patient in response to treatment with
the ICI are molecular factors including cytokines, chemokines,
growth factors, enzymes and soluble receptors.
37. The method of claim 36, wherein the factors are pro-tumorigenic
or pro-metastatic factors, and the pro-tumorigenic factors may be
pro-angiogenic, pro-inflammatory/chemotactic or proliferative
growth factors.
38. The method of claim 37, wherein if there is an increase
(up-regulation) of at least about 1.5-fold in the level of one or
more of the pro-tumorigenic or pro-metastatic factors, then the
prediction is of a non-favorable response of the cancer patient to
the treatment with the ICI, and if there is a decrease
(down-regulation) of at least about 0.5-fold in the level of one or
more of the pro-tumorigenic or pro-metastatic factors, then the
prediction is of a favorable response of the cancer patient to the
treatment with the ICI.
39. The method of claim 38, wherein the selected dominant factor
shows a fold change of .gtoreq.1.5 indicative of a non-favorable
response of the cancer patient to the treatment with the ICI, and
proceeding with the treatment of the patient with said ICI in
combination with an agent that blocks said dominant factor or the
receptor thereof.
40. The method of claim 39, wherein the dominant factor is selected
from factors including amphiregulin, EGF, EGFR, FGF, IFN-.gamma.,
IL-1.beta., IL-2, IL-6, MMP9, PDGF, TNF-.alpha. and VEGF-A.
41. The method of claim 40, wherein the dominant factor is MMP9,
the ICI is an anti-PD-1 or an anti-PD-L1 monoclonal antibody, and
the cancer patient is treated with the ICI in combination with a
MMP9 inhibitor including SB-3CT.
42. The method of claim 40, wherein the dominant factor is
amphiregulin, the ICI is an anti-PD-1 or an anti-PD-L1 monoclonal
antibody, and the cancer patient is treated with the ICI in
combination with an anti-amphiregulin antibody.
Description
CROSS-REFERENCE TO RELATED APPLICATIONS
[0001] The present application is a continuation-in-part of
International Application No. PCT/IL2018/050609, filed Jun. 4,
2018, in which the United States is designated, and is a
non-provisional of the Provisional Application No. 62/594,141,
filed Dec. 4, 2017, and is a non-provisional of the Provisional
Application No. 62/564,392, filed Sep. 28, 2017, and is a
non-provisional of the Provisional Application No. 62/514,851,
filed Jun. 4, 2017, the entire contents of each and all these
applications being hereby incorporated by reference herein in their
entirety as if fully disclosed herein.
FIELD OF THE INVENTION
[0002] The present invention is in the field of oncology and
particularly relates to a method of predicting a personalized
response of a cancer patient to treatment with immune checkpoint
inhibitors, to kits therefor, and to a method of treatment of a
cancer patient with an immune checkpoint inhibitor.
BACKGROUND
[0003] One of the major obstacles in clinical oncology is that
tumors often develop resistance to therapy even when an initial
tumor response to treatment is observed. Many studies have focused
on the contribution of mutations and genetic aberrations in the
tumor cells which promote drug resistance and can explain tumor
re-growth. However, studies have demonstrated that the host, in
response to cancer therapy, generates pro-tumorigenic and
pro-metastatic effects which in turn contribute to tumor re-growth,
and therefore negate the anti-tumor activity of the drug (for
reviews see Katz and Shaked, 2015; Shaked, 2016).
[0004] Host-mediated responses to anti-cancer treatment modalities
may be molecular and/or cellular responses. Upon treatment with
chemotherapeutic drugs, host bone marrow derived cells (BMDCs) are
mobilized from the bone marrow compartment, colonize the treated
tumor and contribute to tumor angiogenesis and cancer re-growth,
thereby promoting therapy resistance (Shaked et al., 2006, 2008).
Cancer therapy also induces pro-tumorigenic activation of various
immune cells such as macrophages and antigen presenting cells
(Beyar-Katz et al., 2016; De Palma and Lewis, 2013; Kim et al.
2012; Ma et al., 2013). Overall, these aforementioned studies
indicate that host-mediated molecular and cellular responses to
different anti-cancer treatments involve the activation or
education of immune cells as well as the secretion of various
pro-tumorigenic factors. These combined effects contribute to tumor
re-growth and resistance to therapy. This relatively new phenomenon
has made a paradigm shift in understanding cancer progression and
resistance to therapy.
[0005] Recently, a new treatment modality, an immunotherapy using
immune checkpoint inhibitors (ICIs), is revolutionizing cancer
therapy. Such immune-modulating drugs have shown remarkable
successes for the treatment of advanced malignancies (including
stage IV) such as melanoma, prostate, non-small cell lung cancer,
renal cell carcinoma and also some hematological malignancies
(Postow et al., 2015). Although the human immune system is capable
of recognizing and mounting a response to cancerous cells, this
response is often circumvented by tumor-derived inhibition
resulting in immune tolerance. In this regard, tumor-infiltrating
lymphocytes (TILs), such as tumor antigen-specific CD8.sup.+
cytotoxic T lymphocytes (CTLs) and natural killer (NK) cells, have
been found to colonize the tumor microenvironment (Gajewski et al.,
2013). Yet, at the tumor site, they completely lack the ability to
act against tumor cells (Ostrand-Rosenberg and Sinha, 2009). This
is due to direct inhibitory effects of factors secreted by cancer
cells, stromal cells or other suppressive immune cells such as
myeloid derived suppressor cells (MDSCs) and T regulatory cells
(Tregs) (Makkouk and Weiner, 2015). For instance, IL-10 is
frequently upregulated in various types of cancer, and was shown to
suppress the immune system (Sato et al., 2011). Thus, identifying
molecules that negatively regulate the immune system against tumor
cells, will lead to the development of immunomodulatory drugs that
support the activation of immune cells against tumors.
[0006] Of specific interest are immune checkpoint proteins, such as
CTLA-4, PD-1 and its ligand, PD-L1. These checkpoint proteins are
expressed by tumor cells or other immune cells and contribute to
the exhaustion of CTLs (Postow et al., 2015; Topalian et al.,
2015). Specifically, they keep immune responses in check, and
inhibit T cell killing effects against tumor cells. As such,
checkpoint inhibitors have been developed in order to inhibit the
immune suppression effects. Currently, antibodies blocking the
immune checkpoints, CTLA-4 and PD-1 or its ligand PD-L1 have been
developed (Pardoll, 2012). These ICIs are currently in use in the
clinic for the treatment of various malignancies with some
promising and remarkable successes (Romano and Romero, 2015).
However, ICIs have shown therapeutic benefit only for a limited
portion of cancer patients (.about.10-20%). For example, pooled
data from clinical studies of ipilimumab, a CTLA-4 blocking
antibody, revealed that the duration of clinical response is around
3 years, and can last up to 10 years. However, this dramatic
therapeutic effect is only observed in a subset of patients
(.about.20%). Thus, the majority of patients exhibit intrinsic
resistance mechanisms to such therapies. Yet, the molecular aspects
that define the subpopulation of patients that are responsive to
ICIs are not fully clear. It has been suggested that markers, such
as PD-L1 expression by tumor cells, mutational burden, and
lymphocytic infiltrates could predict the cancer patients that will
respond to immunotherapy. However, these aforementioned biomarkers
do not always correlate with tumor responsiveness to immunotherapy
or resistance of patients to ICIs. Therefore, additional possible
mechanisms are still unknown.
[0007] It would be highly desirable to unveil host-mediated
cellular and molecular mechanisms that contribute to tumor
resistance to all modalities of cancer therapy including the
promising ICI therapy modality. This will permit development of
strategies to block such unwanted host effects and will improve
therapeutic outcome and delay resistance to cancer therapy.
SUMMARY OF THE INVENTION
[0008] In one aspect, the present invention relates to a method for
identification of a set of host-driven resistance factors to cancer
immunotherapy with one or more immune checkpoint inhibitors
(hereinafter "ICIs") in a biological sample of a cancer patient
treated with said therapy. These factors are Specific Host-Driven
Resistance Factors, namely, they are not generated by intrinsic
resistance of the cancer cells, but are driven by the host, i.e.,
the cancer patient, in response to said cancer therapy using ICIs
and may limit or counteract the effectiveness of the treatment with
the ICIs applied to said patient. The determination of these
factors allows the prediction in a personalized form of the
favorable or non-favorable response of the patient to the treatment
with the ICIs. These factors, herein designated interchangeably
"factors" or "biomarkers", are factors, mainly cytokines,
chemokines, growth factors, soluble receptors, enzymes and other
molecules produced by the host cells, either at different organs or
at the tumor microenvironment, in response to the cancer therapy
with the ICI with which the patient is treated.
[0009] Thus, in certain embodiments, the present invention provides
a method for predicting the response of a cancer patient to
treatment with at least one immune checkpoint inhibitor,
comprising: determining in a biological sample obtained from the
cancer patient at a time period after a session of treatment with
said at least one immune checkpoint inhibitor the levels of a
plurality of factors generated by the cancer patient in response to
said treatment, one or more of the plurality of factors promoting
responsiveness or non-responsiveness of the patient to the
treatment with the ICI, wherein a change in the levels of two or
more of the plurality of factors as compared to a reference level,
predicts a favorable or a non-favorable response of the cancer
patient to the treatment with said at least one immune checkpoint
inhibitor.
[0010] In certain embodiments, the biological sample is blood
plasma. In certain embodiments, the biological sample of the cancer
patient is a whole blood sample. In certain embodiments, the
biological sample is blood serum. In certain embodiments, the
biological sample is peripheral blood mononuclear cells.
[0011] In certain embodiments, the invention provides a method for
predicting the response of a cancer patient to treatment with an
immune checkpoint inhibitor (ICI), the method comprising the steps
of:
[0012] (i) performing an assay on a biological sample selected from
blood plasma, whole blood, blood serum or peripheral blood
mononuclear cells obtained from the cancer patient at a time period
after a session of treatment with said ICI, to determine the levels
of one or more of a plurality of factors induced in the circulation
of said cancer patient in response to treatment with said ICI, said
one or more of the plurality of factors promoting responsiveness or
non-responsiveness of the cancer patient to the treatment with said
ICI;
[0013] (ii) obtaining reference levels for each of the one or more
of the plurality of the induced factors of step (i) in a biological
sample obtained from the cancer patient before said session of
treatment with the ICI;
[0014] (iii) establishing the fold change for each of the one or
more of the plurality of the induced factors of step (i) by
comparing the level of each induced factor of step (i) with the
reference level of step (ii) for the same factor; and
[0015] (iv) determining that the cancer patient has a favorable or
a non-favorable response to the treatment with said ICI based on
the fold change established in step (iii) for one or more of the
plurality of induced factors of step (i).
[0016] In another aspect, the present invention provides a kit
comprising a plurality of antibodies, each antibody of the
plurality of antibodies selectively binding to each of a plurality
of factors that promote responsiveness or non-responsiveness of a
cancer patient to treatment with an immune checkpoint inhibitor,
and instructions for use.
[0017] In a further aspect, the invention provides a method for
treatment of a cancer patient with an immune checkpoint
inhibitor.
BRIEF DESCRIPTION OF THE FIGURES
[0018] FIG. 1A-D demonstrates that plasma and bone marrow cells
derived from anti-PD-1-treated naive BALB/c mice enhance the
metastatic properties of tumor cells. Naive (non-tumor bearing)
8-10 week old BALB/c mice were treated with anti-PD-1 or control
antibodies for 1 week (n=3 mice/group). (A) Invasion and migration
properties of EMT6 cells were assessed in a Boyden chamber assay in
the presence of plasma extracted from control and anti-PD-1-treated
mice. Representative images of invading and migrating cells are
shown. (B) Cell coverage was quantified from the images and fold
increase in cell coverage was calculated. Averages of 3 biological
repeats are shown. (C-D) Bone marrow cells flushed from femurs of
control or anti-PD-1-treated mice were cultured in serum-free DMEM
for 24 hours (1.times.10.sup.6 cells/ml). Conditioned medium was
collected and assessed by zymography to evaluate MMP activity. A
representative zymography blot is shown in (C) and quantification
of MMP9 is shown in (D). The experiment was performed in three
biological repeats. *p<0.05; ***p<0.001, using Student
t-test.
[0019] FIG. 2 A-B shows the effect of plasma derived from
anti-PD-1-treated naive SCID mice on the metastatic properties of
tumor cells in vitro. Naive (non-tumor bearing) 8-10 week old SCID
mice were treated with anti-PD-1 or control antibodies for 1 week
(n=3 mice/group). (A) Invasive properties of EMT6 cells were
assessed in a Boyden chamber assay in the presence of plasma
extracted from control and anti-PD-1-treated mice. Representative
images of invading cells are shown. (B) Percentage of cell coverage
was quantified from the images. Averages of 3 biological repeats
are shown. ***p<0.001, using Student t-test.
[0020] FIG. 3A-D shows the effect of plasma and bone marrow cells
derived from anti-PD-1-treated naive NOD-SCID mice on the
metastatic properties of tumor cells. Naive (non-tumor bearing)
8-10 week old NOD-SCID mice were treated with anti-PD-1 or control
antibodies for 1 week (n=3 mice/group). (A) Invasion and migration
properties of EMT6 cells were assessed in a Boyden chamber assay in
the presence of plasma extracted from control and anti-PD-1-treated
mice. Representative images of invading and migrating cells are
shown. (B) Percentage of cell coverage was quantified from the
images. Averages of 3 biological repeats are shown. (C-D) Bone
marrow cells flushed from femurs of control or anti-PD-1-treated
mice were cultured in serum-free DMEM for 24 hours
(1.times.10.sup.6 cells/ml). Conditioned medium was collected and
assessed by zymography to evaluate MMP activity. A representative
zymography blot is shown in (C) and quantification of MMP9 is shown
in (D). The experiment was performed in three biological repeats.
***p<0.001, using Student t-test.
[0021] FIG. 4A-B shows that EMT6 cells pre-cultured with plasma
from anti-PD-1-treated BALB/c mice increase mortality rate in an
experimental lung metastasis assay. (A-B) EMT6 murine breast
carcinoma cells were pre-cultured for 4 hours in the presence of
plasma derived from control or anti-PD-1-treated BALB/c mice. The
cells were washed and injected intravenously through the tail vein
(2.5.times.10.sup.4 cells/mouse) to naive 8 week old BALB/c mice to
generate an experimental lung metastasis assay. Survival was
assessed over time. Kaplan-Meier survival curves are shown for the
first (A) and second (B) experiments in which n=5 and n=7-8
mice/group were used, respectively. p<0.05 in (A) and p=0.055 in
(B).
[0022] FIG. 5A-B shows the colonization of different host cell
types in Matrigel containing plasma from anti-PD-1-treated mice.
Plasma obtained from control or anti-PD-1-treated mice was mixed
with Matrigel in a 1:10 ratio. Matrigel plugs were implanted into
the flanks of naive 8-10 week old BALB/c mice (n=4 mice/group). (A)
After 10 days, the Matrigel plugs were removed, sectioned and
subsequently stained with H&E (left micrographs) or CD31, an
endothelial cell marker (in red, right micrographs). (B) In a
parallel experiment, Matrigel plugs were prepared as single cell
suspensions. Cell suspensions were evaluated for the indicated
immune cell types using flow cytometry. *p<0.05;
**p<0.01;***p<0.001, as assessed by Student t-test.
DETAILED DESCRIPTION
[0023] Before describing the methods and kits of the invention, it
should be understood that this invention is not limited to the
particular methodology and protocols as described herein. It is
also to be understood that the terminology used herein is for the
purpose of describing particular embodiments of the invention only
and, if not defined otherwise, it is not intended to limit the
scope of the present invention which will be recited in the
appended claims.
[0024] It must also be noted that as used herein and in the
appended claims, the singular form "a", "an", and "the" include
plural reference unless the context clearly dictates otherwise.
[0025] As used herein, the term "a cancer therapy" may be used
interchangeably with the term "a cancer therapy modality", and
include plural reference, namely, one single modality therapy or a
combination of two or more modality therapies.
[0026] As used herein, the terms "induced", "driven" and
"generated" are used interchangeably to denote the factors induced
into the circulation by the cancer patient in response to the
cancer therapy ("host-response").
[0027] In accordance with the present invention, a method is
provided for predicting the response of a cancer patient to
treatment with at least one immune checkpoint inhibitor (ICI),
comprising: determining in a biological sample obtained from the
cancer patient at a time period after a session of treatment with
said at least one immune checkpoint inhibitor the levels of a
plurality of factors generated by the cancer patient in response to
said treatment, one or more of the plurality of factors promoting
responsiveness or non-responsiveness of the patient to the
treatment, wherein a change in the levels of two or more of the
plurality of factors, as compared to a reference level, predicts a
favorable or a non-favorable response of the cancer patient to the
treatment with said at least one immune checkpoint inhibitor.
[0028] The biological sample may be whole blood sample, blood
plasma, blood serum, or peripheral blood mononuclear cells. In
certain embodiments, the biological sample is blood plasma.
[0029] In cancer therapy, a cycle of treatment means that the drug
is administered to the patient at one point in time (for example,
injections over a day or two) and then there is some time (e.g., 1,
2 or 3 weeks) with no treatment. The treatment and rest time make
up one treatment cycle. When the patient gets to the end of the
cycle, it starts again with the next cycle. A series of cycles of
treatment is called a course.
[0030] As used herein, "a session of treatment" refers to the "one
point in time" when the ICI is administered to the patient at the
beginning of a cycle of treatment.
[0031] As used herein, the term "an immune checkpoint inhibitor
(ICI)" refers to a single ICI, a combination of ICIs and a
combination of an ICI with another cancer therapy.
[0032] As used herein, the term "treatment" refers to "treatment
with an ICI" alone or in combination with another ICI or another
cancer therapy.
[0033] In certain embodiments, the invention relates to a method
for predicting the response of a cancer patient to treatment with
an immune checkpoint inhibitor (ICI), the method comprising the
steps of:
[0034] (i) performing an assay on a biological sample selected from
blood plasma, whole blood, blood serum or peripheral blood
mononuclear cells obtained from the cancer patient at a time period
after a session of treatment with said ICI, to determine the levels
of one or more of a plurality of factors induced in the circulation
of said cancer patient in response to treatment with said ICI, said
one or more of the plurality of factors promoting responsiveness or
non-responsiveness of the cancer patient to the treatment with said
ICI;
[0035] (ii) obtaining reference levels for each of the one or more
of the plurality of the induced factors of step (i) in a biological
sample obtained from the cancer patient before said session of
treatment with the ICI;
[0036] (iii) establishing the fold change for each of the one or
more of the plurality of the induced factors of step (i) by
comparing the level of each induced factor of step (i) with the
reference level of step (ii) for the same factor; and
[0037] (iv) determining that the cancer patient has a favorable or
a non-favorable response to the treatment with said ICI based on
the fold change established in step (iii) for one or more of the
plurality of induced factors of step (i).
[0038] In preferred embodiments, both the biological samples of
steps (i) and (ii) are blood plasma.
[0039] In certain embodiments of the invention, the session of
treatment with the ICI is one of multiple sessions of treatment. In
certain embodiments, the one of multiple sessions of treatment with
the ICI is the first session of treatment with said ICI, the
biological sample of step (i) is obtained from the cancer patient
at about 20, 24, 30, 36, 40, 48, 50, 60, 72 hours or more,
including up to one week or more, up to three weeks or more, after
said first session of treatment, and the reference biological
sample of step (ii) is obtained from the cancer patient at a time
point including at about 72 hours or less, including at about 60,
50, 48, 40, 36, 30, 24 or 20 hours or less or just before said
first session of treatment with the ICI.
[0040] In certain embodiments, the one of multiple sessions of
treatment of the cancer patient with the ICI is the first session
of treatment, when the treatment with the ICI is started. In this
case, the reference/baseline sample of step (ii), preferably blood
plasma, is obtained from the cancer patient at a time point before
starting the treatment including at about 72 hours or less,
including at about 60, 50, 48, 40, 36, 30, 24 or 20 hours or just
before said first session of treatment with the ICI. The comparison
is then made between the concentration levels of the factors
determined in the biological sample, preferably blood plasma,
obtained from the cancer patient at about 20, 24, 30, 36, 40, 48,
50, 60, 72 hours or more, including up to one week or more, up to
three weeks or more, after said first session of treatment with the
ICI.
[0041] In certain other embodiments of the invention, the session
of treatment of the cancer patient with the ICI is one of multiple
sessions of treatment that is not the first session of treatment
with the ICI. In this case, the biological sample is obtained from
the cancer patient at any time point between two consecutive
sessions of treatment with the ICI and serves simultaneously as the
biological sample of step (i) and the reference biological sample
according to step (ii) for the next session assay according to step
(i). The time between two consecutive sessions of treatment depends
on the treatment protocol approved for the specific ICI and may be,
for example, of 2 or 3 weeks, depending on the ICI, and the
biological sample may be obtained at day 1, 2, 3, 7, 14, or 21 days
between two consecutive sessions.
[0042] In accordance with the invention, the levels of the
plurality of factors generated by the host/cancer patient in
response to the treatment with the immune checkpoint inhibitor are
determined in the biological sample, preferably blood plasma,
obtained from the patient after treatment with ICI. The value
(factor concentration in pg/mL) obtained for each factor is then
compared with a reference level, which is the baseline level of
concentration of the same factor determined in a biological sample,
preferably blood plasma, obtained previously from the same cancer
patient (hereinafter "reference/baseline sample"). The change in
the level of one or more of the factors identified in the
biological sample obtained from the cancer patient after the
treatment with the ICI compared to the reference/baseline level, is
defined by the fold change for each factor. The fold change for
each factor is determined by calculating the ratio of treatment:
reference/baseline values for the factor.
[0043] In certain embodiments, the fold change denotes an increase
(up-regulation) of at least 1.5-fold or a decrease
(down-regulation) of at least 0.5-fold in the level of each of the
one or more of the pro-tumorigenic or pro-metastatic factors
generated by the cancer patient in response to the treatment with
the ICI. A fold-change of .gtoreq.1.5 indicating upregulation or a
fold change of .ltoreq.0.5 indicating down-regulation in the level
of each of the one or more of the plurality of pro-tumorigenic or
pro-metastatic factors induced in the circulation of the cancer
patient in response to the treatment with the ICI, these values
being considered significant and predictive of a non-favorable or
favorable response of the cancer patient to the treatment with the
said ICI.
[0044] The prediction of a favorable or a non-favorable response of
the cancer patient to the treatment with the ICI is based on
significant fold changes of one or more, optionally two or more,
three or more, four or more, five or more, six or more, seven or
more, eight or more, nine or more, ten or more, eleven or more,
twelve or more, thirteen or more, fourteen or more, fifteen or
more, twenty or more, or twenty-five or more, of the induced
factors.
[0045] The factors/biomarkers induced into the circulation of the
cancer patient in response to treatment with the ICI include
molecular factors such as cytokines, chemokines, growth factors,
enzymes and soluble receptors.
[0046] The factors may be pro-tumorigenic or pro-metastatic
factors. The pro-tumorigenic factors may be pro-angiogenic,
pro-inflammatory/chemotactic or proliferative growth factors.
[0047] In accordance with the invention, the change in the level of
one or more of the factors/biomarkers identified in the biological
sample obtained from the cancer patient after the treatment with
the ICI compared to the reference/baseline level, is defined by the
fold change for each factor. The fold change for each factor is
determined by calculating the ratio of treatment:
reference/baseline values for the factor.
[0048] In certain embodiments, the change in the level of the
factors is an increase (up-regulation) of at least 1.5-fold or a
decrease (down-regulation) of at least 0.5-fold in the level of
each of the one or more of the factors generated by the cancer
patient in response to the treatment with the ICI. A fold change of
.gtoreq.1.5 indicating upregulation of the factor or a fold change
of .ltoreq.0.5 indicating down-regulation of the factor are
considered significant according to the invention and and
predictive of a favorable or a non-favorable response of the cancer
patient to the treatment with the ICI.
[0049] The change in the level of one or more of the
factors/biomarkers identified in the biological sample obtained
from the cancer patient after the treatment with ICI compared to
the reference/baseline level, if significant, predicts a favorable
or a non-favorable response of said cancer patient to said cancer
therapy. The fold change is considered significant if it is of at
least about 1.5 fold or higher, i.e., .gtoreq.1.5 (up-regulation),
or if it is at least about 0.5 fold or lower, i.e., .ltoreq.0.5
(down-regulation). As used herein, the fold change "considered
significant" is predictive of a favorable or a non-favorable
response of the cancer patient to said treatment with ICI.
[0050] The fold change is determined for all circulating factors in
the patient's biological sample. The prediction of a favorable or a
non-favorable response of the cancer patient to the treatment will
be based on the significant fold changes of one or more, optionally
two or more, three or more, four or more, five or more, six or
more, seven or more, eight or more, nine or more, ten or more,
eleven or more, twelve or more, thirteen or more, fourteen or more,
fifteen or more, twenty or more, or twenty-five or more, of the
induced factors.
[0051] In certain embodiments, the change is an increase
(up-regulation) of at least about 1.5 fold in the level of one or
more of the biomarkers. If the increase is in the level of
biomarkers that are pro-tumorigenic or pro-metastatic, this
indicates a non-favorable response of the cancer patient to the
treatment.
[0052] In certain embodiments, the change is a decrease
(down-regulation) of at least about 0.5 fold in the level of one or
more of the biomarkers. If the decrease is in the level of
biomarkers that are pro-tumorigenic or pro-metastatic, this
indicates a favorable response of the cancer patient to the
treatment.
[0053] In certain embodiments, the session of treatment is the
first session of a plurality of sessions of treatment of the cancer
patient, when the treatment is started. In this case, the
comparison is between the factors determined in the biological
sample, preferably blood plasma, obtained from the cancer patient
after first starting treatment with the ICI, and the same factors
found in the reference/baseline biological sample, preferably blood
plasma, obtained from the cancer patient before starting treatment
with the ICI. The results may assist the medical oncologists
treating the patient to decide if or how to continue the treatment
of the cancer patient.
[0054] In certain embodiments, the method of the invention is
performed for monitoring treatment response in a cancer patient
being treated with an ICI. In this case, the session of treatment
is one of the sessions of several sessions of treatment, but not
the first one. The results will assist the medical oncologist in
their decisions if or how to continue the treatment.
[0055] In certain embodiments, the fold change determined for
pro-tumorigenic factors is predictive of the patient's favorable
response to the cancer therapy and the decision may be to continue
the treatment with the same ICI as scheduled.
[0056] In certain embodiments, the fold change determined for
pro-tumorigenic factors is predictive of the patient's
non-favorable response to the ICI. In this case, depending on the
specific biological activity of the pro-tumorigenic factors, the
decision may be to continue the treatment with the same ICI but
with the addition of a drug that blocks the biological activity of
the tumorigenic factors, for example, by adding to the treatment an
anti-inflammatory drug if the factors are pro-inflammatory or by
adding to the treatment an anti-angiogenic drug if the factors are
pro-angiogenic.
[0057] In certain embodiments, the fold change determined for
pro-tumorigenic factors is predictive of the patient's
non-favorable response to the ICI used and the medical oncologist's
decision may be to change the treatment using a different ICI, or
to use a combination of two ICIs, or a combination of the ICI with
another drug used in cancer therapy.
[0058] Immune checkpoints are regulators of immune activation. They
play a key role in maintaining immune homeostasis and preventing
autoimmunity. In cancer, immune checkpoint mechanisms are often
activated to suppress the nascent anti-tumor immune response.
Immune checkpoint molecules are considered as good targets for
cancer immunotherapy. Immune checkpoint inhibitors (ICI) that cause
blockade of the immune checkpoint molecules are considered good
candidates for the development of drugs for cancer immunotherapy
with the potential for use in multiple types of cancers and are
already in use or are under development.
[0059] Examples of immune checkpoints that are candidates as
targets for development of immune checkpoint inhibitor (ICI) drugs
include PD-1 (Programmed Death-1) that has two ligands, PD-L1 and
PD-L2; CTLA-4 (Cytotoxic T-Lymphocyte-Associated protein 4); A2AR
(Adenosine A2A receptor), also known as ADORA2A; BT-H3, also called
CD276; BT-H4, also called VTCN1; BT-H5; BTLA (B and T Lymphocyte
Attenuator), also called CD272; IDO (Indoleamine 2,3-dioxygenase);
MR (Killer-cell Immunoglobulin-like Receptor); LAG-3 (Lymphocyte
Activation Gene-3); TDO (Tryptophan 2,3-dioxygenase); TIM-3 (T-cell
Immunoglobulin domain and Mucin domain 3); VISTA (V-domain Ig
suppressor of T cell activation).
[0060] In certain embodiments of the invention, the ICI is a
monoclonal antibody (mAb) against PD-1 or PD-L1 that
neutralizes/blocks the PD-1 pathway. In certain embodiments, the
anti-PD-1 mAb is Pembrolizumab (Keytruda; formerly called
lambrolizumab), approved or tested for treatment of advanced or
unresectable melanoma, metastatic non-small cell lung cancer
(NSCLC), renal cell carcinoma (RCC), and recurrent squamous cell
carcinoma of the head and neck (SCCH). In certain embodiments, the
anti-PD-1 mAb is Nivolumab (Opdivo), approved or tested for NSCLC,
RCC, melanoma and colorectal cancer (CRC). In certain embodiments,
the anti-PD-1 mAb is Pidilizumab (CT0011), approved or tested for
non-Hodgkin's lymphoma, chronic lymphocytic leukemia, Hodgkin's
lymphoma, multiple myeloma, and acute myeloid leukemia. In certain
embodiments, the anti-PD-1 mAb is REGN2810, AMP-224, MEDI0680, or
PDR001.
[0061] In certain other embodiments of the invention, the immune
checkpoint inhibitor is a mAb against PD-L1. In certain
embodiments, the anti-PD-L1 mAb is Atezolizumab (Tecentriq),
Avelumab (Bavencio), or Durvalumab (Imfinzi), approved for multiple
cancers. Atezolizumab is being tested in combination with one or
two other cancer agents such as bevacizumab, gemcitabine,
cisplatin, docetaxel, paclitaxel, vinflunine entinostat,
daratumumab, MPDL3280A, carboplatin, Nab-paclitaxel, Radium-223
dichloride, obinutuzumab, for multiple cancers.
[0062] In certain other embodiments of the invention, the ICI is a
mAb antibody against CTLA-4. In certain embodiments, the
anti-CTLA-4 Ipilimuniab (Yervoy), approved or tested for
advanced/metastatic melanoma and castrate-resistant prostate
cancer. In certain other embodiments, the anti-CTLA-4 mAb is
Tremelimumab (formerly ticilimumab).
[0063] In certain embodiments, the ICI is an inhibitor including:
(i) anti-B7-H3, such as MGA271; (ii) anti-IDO, such as epacadostat;
(iii) anti-KIR, such as Lirilumab; (iv) anti-LAG-3, such as
Relatlimab (BMS-986016), LAG 525, REGN3767; (v) anti-TIM-3, such as
TSR022 or MBG453; and (vi) anti-VISTA, such as JNJ 61610588.
[0064] In certain embodiments, a combination of two ICIs is used
according to the invention. In certain embodiments, the combination
comprises an anti-PD-1 and an anti-CTLA-4, e.g.,
Nivolumab-Ipilimumab and REGN2810-Ipilimumab. In certain
embodiments, the combination comprises an anti-PD-L1 and an
anti-CTLA-4, e.g., Durvalumab-Tremelimumab. In certain embodiments,
the combination comprises an anti-PD-1 and an anti-PD-L1, e.g.,
Nivolumab-Atezolimumab. In certain embodiments, the combination
comprises an anti-LAG-3 and an anti-PD-1, e.g.,
Relatlimab-Nivolumab or REGN3767-REGN2810. In certain embodiments,
the combination comprises an anti-PD-1 and an IDO inhibitor, e.g.,
Pembrolizumab and Epacadostat and Nivolumab-Epacadostat.
[0065] Costimulatory molecules such as CD137 (4-1BB), CD134 (OX40),
glucocorticoid-induced TNFR (GiTR CD357), and CD40 are expressed by
activated T cells, activated natural killer (NK) cells, natural
killer T (NKT) cells, Tregs, and other immune cells. The inhibition
of the immune checkpoint PD-1 and stimulation of costimulatory
molecules by agonist antibodies are complementary strategies to
enhance immune responses and therefore provide a strong rationale
for use in combination. Thus, in certain embodiments, the invention
encompasses a combination of an ICI with an agonistic mAb against
T-cell co-stimulatory molecules including an anti-ICOS mAb, e.g.,
MEDI-570 or BMS-986226: an anti-OX40 mAb e.g., MOXR0916, KHK4083,
MEDI0562 or MEDI6469; an anti-CD40 mAb; and an anti-CD137 (4-IBB)
mAb, e.g., Urelumab or Utomilumab.
[0066] In certain embodiments of the invention, the ICI is
administered in combination with one or more conventional cancer
therapy including chemotherapy, targeted cancer therapy and
radiotherapy. Combinations of ICI and radiation therapy have been
studied in multiple clinical trials.
[0067] In certain embodiments, the ICI is used in combination
chemotherapy that may be with a single or a combination of
chemotherapy drugs, or metronomic chemotherapy. The combinations
Pembrolizumab+carboplatin+paclitaxel,
Pembrolizumab+gemcitabine+docetaxel,
Nivolumab+gemcitabine+cisplatin, Ipilimumab+carboplatin+paclitaxel,
and other combinations were tested or are being tested in clinical
trials.
[0068] In certain embodiments, the ICI therapy is used in
combination with targeted cancer therapy, sometimes called
"molecularly targeted therapy". In certain embodiments, the
targeted therapy drugs are small molecules such as bortezormib
(Velcade), sunitinib (Sutent). In certain embodiments, the targeted
therapy drugs are monoclonal antibodies such as bevacizumab
(Avastin), panitumumab (Vectibix), daratumumab (Darzalex). In
certain embodiments, an anti-PD-1 is used in combination with
sunitinib (Sutent) or pazopanib (Votrient) that was tested for
treatment of RCC, or a combination of anti-CTLA-4 ipilimumab with
BRAF inhibitor dabrafenib (Tafinlar).
[0069] In certain embodiments, the ICI therapy is used in
combination with anti-angiogenic therapy, for example, with a mAb
that targets VEGF. Thus, the combination may be of Ipilimumab and
bevacizumab.
[0070] In certain embodiments, the ICI therapy is used in
combination with other immunotherapies such as cancer vaccines,
immunomodulators, immunostimulatory cytokines, e.g., GM-CSF,
IFN-.alpha., TGF-.beta., IL-10, IL-18, and IL-21, or oncolytic
viruses. In certain embodiments, anti-CTLA-4 ipilimumab or
anti-PD-1 pembrolizumab is used in combination with oncolytic virus
talimogene laherparepvec (T-VEC).
[0071] In accordance with the invention, the cancer therapy is
related to all types of cancer, primary or metastatic, in all
stages of the disease. The cancer may be selected from sarcomas,
carcinomas, myelomas, lymphomas and leukemias. In certain
embodiments, the cancer is of the sarcoma type, e.g. soft tissue
sarcoma, osteosarcoma, in certain embodiments, the cancer is a
carcinoma including, but without being limited to, melanoma, brain,
head, neck, bone, nasopharyngeal, liver, gastrointestinal, biliary,
bile duct, esophageal, colon, rectal, colorectal, ovarian, breast,
cervical, prostate, renal, penile, testicular, skin, lung, chest,
pancreatic, thymus, thyroid, or bladder cancer.
[0072] In certain embodiments, the cancer is a lymphoma, a cancer
of the lymphatic system that may be a Hodgkin lymphoma or a
non-Hodgkin lymphoma. The non-Hodgkin lymphoma may be B-cell
lymphoma or T-cell lymphoma.
[0073] In certain embodiments, the cancer is leukemia, a cancer of
the body's blood-forming tissues, including the bone marrow and the
lymphatic system. In certain embodiments, the leukemia is selected
from acute lymphocytic leukemia (ALL), acute myeloid leukemia
(AML), chronic lymphocytic leukemia (CLL) or chronic myeloid
leukemia (CML). In certain embodiments, the cancer is multiple
myeloma.
[0074] In certain embodiments, the cancer is non-small cell lung
cancer (NSCLC). In certain embodiments, the cancer is advanced
(stage III or IV) or metastatic NSCLC.
[0075] In certain embodiments, the cancer is metastatic melanoma,
renal-cell carcinoma (RCC), classic Hodgkin's lymphoma (HL),
bladder carcinoma, Merkel cell carcinoma, head and neck cancer, or
solid tumors with mismatch repair-deficiency
[0076] The host-driven factors/biomarkers identified by the method
of the invention after administration of an immune checkpoint
inhibitor to a cancer patient are specific to: (i) the cancer
patient; and (ii) the immune checkpoint inhibitor. This is the
"host response" that provides specific information about the cancer
patient and allows the prediction in a personalized form to help
diagnose, plan treatment, find out how well treatment is working,
or make a prognosis
[0077] If the treatment is with one single ICI, the factors
generated by the host/patient are specific to this particular ICI.
If the treatment is carried out with a combination of two ICIs, the
factors generated by the host/patient are specific to this
combination of ICIs. If treatment is with the ICI in combination
with another cancer therapy, the factors generated by the
host/patient are specific to this combination.
[0078] In certain embodiments, the biomarkers are molecular factors
such as cytokines, chemokines, growth factors, enzymes or soluble
receptors. Some of these factors induce cells that affect the tumor
and contribute to tumor angiogenesis and cancer re-growth, thereby
promoting resistance to the therapy used. Examples of such cells
include bone-marrow derived cells (BMDCs) that are mobilized from
the bone-marrow compartment by cytokines and growth factors such as
G-CSF and SDF-1.alpha., and subsequently colonize the treated
tumors and promote cancer therapy resistance, particularly, but not
exclusively, chemotherapy resistance. Other cells are immune cells
such as macrophages and antigen-presenting cells, or stromal cells
within the tumor microenvironment which play a pivotal role in
tumor progression.
[0079] The host-mediated cellular and molecular mechanisms that
contribute to tumor resistance to a cancer therapy are based on the
biological functions of the factors and/or cells generated in the
host by the particular cancer therapy. Each factor may exhibit one
or more biological functions or activities.
[0080] In certain embodiments, the factors are tumorigenic and
contribute to tumor growth. In certain embodiments, the tumorigenic
factors are pro-angiogenic. In other embodiments, the tumorigenic
factors are pro-inflammatory/chemotactic. In yet other embodiments,
the tumorigenic factors are proliferative growth factors.
[0081] In certain embodiments, the pro-angiogenic factors include,
without being limited to, ANG (angiogenin); angiopoietin-1;
angiopoietin-2; bNGF (basic nerve growth factor); cathepsin S;
Galectin-7; GCP-2 (granulocyte chemotactic protein, CXCL6); G-CSF
(granulocyte-colony stimulating factor); GM-CSF
(granulocyte-macrophage colony stimulating factor, also known as
colony-stimulating factor 2, CSF2); PAI-1 (plasminogen activator
Inhibitor-1); PDGF (platelet-derived growth factor) selected from
PDGF-AA, PDGF-BB, PDGF-AB; PlGF (or PLGF, placental growth factor);
PlGF-2; SCF (stem-cell factor); SDF-1(CXCL12, stromal cell-derived
factor-1); Tie2 (or TIE-2, an endothelial receptor tyrosine
kinase); VEGF (vascular endothelial growth factor) selected from
VEGF-A, VEGF-C and VEGF-D; VEGF-R1; VEGF-R2; VEGF-R3.
[0082] In certain embodiments, the pro-inflammatory and/or
chemotactic factors include, without being limited to, 6Ckine
(CCL21, Exodus-2); angiopoietin-1; angiopoietin-2; BLC (CXCL13, B
lymphocyte chemoattractant or B cell-attracting chemokine 1
(BCA-1); BRAK (CXCL14); CD186 (CXCR6); ENA-78 (CXCL5, Epithelial
cell derived neutrophil activating peptide 78); Eotaxin-1 (CCL11);
Eotaxin-2 (CCL24); Eotaxin-3 (CCL26); EpCAM (Epithelial cell
adhesion molecule); GDF-15 (growth differentiation factor 15, also
known as macrophage inhibitory cytokine-1, MIC-1); GM-CSF; GRO
(growth-regulated oncogene); HCC-4 (CCL16, human CC chemokine 4);
I-309 (CCL1); IFN-.gamma.; IL-1.alpha.; IL-1.beta.; IL-1R4 (ST2);
IL-2; IL-2R; IL-3; IL-3R.alpha.; IL-5; IL-6; IL-6R; IL-7; IL-8;
IL-8 RB (CXCR2, interleukin 8 receptor, beta); IL-11; IL-12;
IL-12p40; IL-12p70; IL-13; IL-13 R1; IL-13R2; IL-15; IL-15Ra;
IL-16; IL-17; IL-17C; IL-17E; IL-17F; IL-17R; IL-18; IL-18BPa;
IL-18 R.alpha.; IL-20; IL-23; IL-27; IL-28; IL-31; IL-33; IP-10
(CXCL10, interferon gamma-inducible protein 10); I-TAC (CXCL11,
Interferon-inducible T-cell alpha chemoattractant); LIF (Leukemia
inhibitory factor); LIX (CXCL5, lypopolysaccharide-induced CXC
chemokine); LRP6 (low-density lipoprotein (LDL) receptor-related
protein-6); MadCAM-1 (mucosal addressin cell adhesion molecule 1);
MCP-1(CCL2, monocyte chemotactic protein 1); MCP-2 (CCL8); MCP-3
(CCL7); MCP-4 (CCL13); M-CSF (macrophage colony-stimulating factor,
also known as colony stimulating factor 1 (CSF1); MIF (macrophage
migration inhibitory factor); MIG (XCL9, Monokine induced by gamma
interferon); MIP-1 gamma (CCL9, macrophage inflammatory protein-1
gamma); MIP-la (CCL3); MIP-10; MIP-16 (CCL15); MIP-3a (CCL20);
MIP-30 (CCL19); MPIF-1 (CCL23, Myeloid progenitor inhibitory factor
1); PARC (CCL18, pulmonary and activation-regulated chemokine); PF4
(CXCL4, platelet factor 4); RANTES (CCL5, regulated on activation,
normal T cell expressed and secreted); Resistin; SCF; SCYB16
(CXCL16, small inducible cytokine B16); TACI (transmembrane
activator and CAML interactor); TARC (CCL17, CC thymus and
activation related chemokine); TSLP (Thymic stromal lymphopoietin;
TNF-.alpha. (tumor necrosis factor-.alpha.); TNF R1; TRAIL-R4
(TNF-Related Apoptosis-Inducing Ligand Receptor 4); TREM-1
(Triggering Receptor Expressed On Myeloid Cells 1).
[0083] In certain embodiments, the proliferative factors include,
without being limited to, Activin A; Amphiregulin; Axl (AXL, a
receptor tyrosine kinase); BDNF (Brain-derived neurotrophic
factor); BMP4 (bone morphogenetic protein 4); cathepsin S; EGF
(epidermal growth factor); FGF-1 (fibroblast growth factor 1);
FGF-2 (also known as bFGF, basic FGF); FGF-7; FGF-21; Follistatin
(FST); Galectin-7; Gas6 (growth arrest-specific gene 6); GDF-15;
HB-EGF (heparin-binding EGF); HGF; IGFBP-1 (Insulin-like growth
factor binding protein-1); IGFBP-3; LAP (Latency-associated
peptide); NGF R (nerve growth factor receptor); NrCAM (neuronal
cell adhesion molecule); NT-3 (neurotrophin-3); NT-4; PAI-1;
TGF-.alpha. (transforming growth factor-.alpha.); TGF-.beta.; and
TGF-.beta.3; TRAIL-R4 (TNF-Related Apoptosis-Inducing Ligand
Receptor 4).
[0084] In certain embodiments, the pro-metastatic factors include,
without being limited to, ADAMTS1 (A disintegrin and
metalloproteinase with thrombospondin motifs 1); cathepsin S;
FGF-2; Follistatin (FST); Galectin-7; GCP-2; GDF-15; IGFBP-6; LIF;
MMP-9 (Matrix metallopeptidase 9, also known as 92 kDa gelatinase
or gelatinase B (GELB); pro-MMP9; RANTES (CCL5); SDF-1 (stromal
cell-derived factor-1, also known as CXCL12) and its receptor
CXCR4.
[0085] The factors may also be anti-tumorigenic factors, e.g.,
anti-angiogenic, anti-inflammatory and/or anti-proliferative growth
factors.
[0086] In certain embodiments, the circulating factors indicating a
host response to ICI include, but are not limited to, ADAMTS1,
amphiregulin; Axl; CCL5/RANTES; CCL17/TARC; EGF; Eotaxin-2; FGF-21;
Gas6; G-CSF; GM-CSF; HGF; IFN-gamma; IL-1Ralpha; IL-2; IL-6; IL-7;
IL-10; IL-12p40; IL-13; IL-33; I-TAC; MadCAM-1; MCP-5; TACI; M-CSF;
MMP-9; PDGF-BB; pro-MMP9; SCF.
[0087] In accordance with the present invention, many of the
factors that were upregulated in response to anti-PD-1 treatment
are key players in pro-tumorigenic and pro-metastatic processes
such as angiogenesis, inflammation, chemotaxis and proliferation.
Upregulated pro-angiogenic factors include: G-CSF; GM-CSF; and
PDGF-BB. Up-regulated pro-inflammatory and/or chemotactic factors
include: CCL17/TARC; CCL5/RANTES; G-CSF; GM-CSF; IFN-gamma;
IL-1Ralpha; IL-2; IL-6; IL-7; IL-10; IL-12p40; IL-13; IL-33; and
M-CSF. Upregulated proliferative growth factors include: FGF-21;
Gas6; and HGF. Upregulated pro-metastatic factors include:
MMP-9.
[0088] In accordance with the present invention, many of the
factors that were upregulated in response to anti-PD-L1 treatment
are key players in pro-tumorigenic and pro-metastatic processes
such as inflammation, chemotaxis and proliferation. Upregulated
pro-angiogenic factors include: G-CSF; and SCF. Upregulated
pro-inflammatory and/or chemotactic factors include: Eotaxin-2;
G-CSF; IL-1ra; IL-6; IL-7; IL-33; I-TAC; MadCAM-1; MCP-5; SCF; and
TACI. Upregulated proliferative growth factors include:
amphiregulin; Axl; EGF; and HGF. Upregulated pro-metastatic factors
include: ADAMTS1 and pro-MMP9.
[0089] In another aspect, the present invention provides a kit
comprising a plurality of antibodies, each antibody of the
plurality of antibodies selectively binding to each of a plurality
of factors that promote responsiveness or non-responsiveness of a
cancer patient to treatment with an immune checkpoint inhibitor,
and instructions for use.
[0090] In certain embodiments, the kit is any type of antibody
array to detect the levels of proteins. In certain embodiments, the
kit is a sandwich or enzyme-linked immunosorbent assay (ELISA) that
uses solid-phase enzyme immunoassay (EIA) to detect the presence of
a substance, usually an antigen, in a liquid sample or wet sample.
According to the present invention, this liquid sample is a
biological sample obtained from a cancer patient undergoing
treatment with an ICI.
[0091] In certain embodiments, the kit comprises a plurality of
human monoclonal antibodies, each binding specifically to a
pro-tumorigenic factor having pro-angiogenic,
pro-inflammatory/chemotactic, proliferative and/or pro-metastatic
activity, at least some of these pro-tumorigenic factors being
factors that have been previously identified according to the
present invention to be predictive of a favorable or a
non-favorable response of a cancer patient to treatment with an
immune checkpoint inhibitor. The kit will of course comprise
additional antibodies for binding to potential candidates
pro-tumorigenic factors. The numbers of monoclonal antibodies in
the kit will be determined according to the producer's
decision.
[0092] Thus, in certain embodiments, the kit of the invention
comprises an array of monoclonal antibodies, at least 30 of said
monoclonal antibodies each specifically binds to a factor selected
from the following 30 factors: ADAMTS1, amphiregulin; Axl;
CCL5/RANTES; CCL17/TARC; EGF; Eotaxin-2; FGF-21; Gas6; G-CSF;
GM-CSF; HGF; IFN-gamma; IL-1Ralpha; IL-2; IL-6; IL-7; IL-10;
IL-12p40; IL-13; IL-33; I-TAC; MadCAM-1; MCP-5; TACI; M-CSF; MMP-9;
PDGF-BB; pro-MMP9; and SCF.
[0093] In certain preferred embodiments, the kit is for use
according to the present invention. In another aspect, the present
invention provides a method for treating a cancer patient with an
immune checkpoint inhibitor (ICI).
[0094] In one embodiment, there is provided a method of treating a
cancer patient with an immune checkpoint inhibitor (ICI), the
method comprising the steps of:
[0095] (i) performing an assay on a biological sample obtained from
the cancer patient after a session of treatment with the ICI to
determine the levels of one or more factors induced in the
circulation of said cancer patient by the ICI;
[0096] (ii) establishing the fold change for each of the one or
more factors of (i) by comparing the level of each of the one or
more factors of (i) with a reference level for each of the one or
more factors of (i) in a biological sample obtained from the cancer
patient before said session of treatment with the ICI; and
[0097] (iiia) if the cancer patient has a non-favorable response to
the treatment with said ICI based on the fold change of the level
of the one or more factors established in (ii), then select a
dominant factor among the one or more factors established in (ii)
and treat the patient with the ICI in combination with an agent
that blocks the dominant factor; or
[0098] (iiib) if the cancer patient has a favorable response to the
treatment with said ICI based on the fold change of the level of
the one or more factors established in (ii), then continue treating
the patient with the ICI.
[0099] In another embodiment, there is provided a method of
treating a cancer patient with an ICI, the method comprising the
steps of:
[0100] (i) performing an assay on a biological sample selected from
blood plasma, whole blood, blood serum or peripheral blood
mononuclear cells obtained from the cancer patient at a time period
after a session of treatment with said ICI, to determine the levels
of one or more of a plurality of factors induced in the circulation
of said cancer patient in response to treatment with said ICI, said
one or more of the plurality of factors promoting responsiveness or
non-responsiveness of the cancer patient to the treatment with said
ICI;
[0101] (ii) obtaining reference levels for each of the one or more
of the plurality of the induced factors of step (i) in a biological
sample selected from blood plasma, whole blood, blood serum or
peripheral blood mononuclear cells, obtained from the cancer
patient before said session of treatment with the ICI;
[0102] (iii) establishing the fold change for each of the one or
more of the plurality of the induced factors of step (i) by
comparing the level of each induced factor of step (i) with the
reference level of step (ii) for the same factor;
[0103] (iv) determining that the cancer patient has a favorable or
a non-favorable response to the treatment with said ICI based on
the fold change established in step (iii) for one or more of the
plurality of induced factors of step (i); and
[0104] (iva) if the cancer patient has a non-favorable response to
the treatment with said ICI based on the fold change established in
(iii) for one or more of the plurality of the induced factors, then
selecting a dominant factor among the one or more factors showing a
fold change indicative of said non-favorable response, and treating
the patient with the ICI in combination with an agent that blocks
the dominant factor; or
[0105] (ivb) if the cancer patient has a favorable response to the
treatment with said ICI based on the fold change of the level of
the one or more factors established in (iii), then continuing the
treatment of the cancer patient with the same ICI.
[0106] The biological samples of steps (i) and (ii) must be of the
same type, and preferably they are both blood plasma.
[0107] According to the invention, when the session of treatment
with the ICI is the first session of treatment with the ICI, the
biological sample of step (i) is obtained from the cancer patient
at about 20, 24, 30, 36, 40, 48, 50, 60, 72 hours or more,
including up to one week or more or up to three weeks or more,
after said first session of treatment, and the reference biological
sample of step (ii) is obtained from the cancer patient at a time
point including at about 72 hours or less, including at about 60,
50, 48, 40, 36, 30, 24, 20 hours or less or just before said first
session of treatment with the ICI.
[0108] When the session of treatment with the ICI is one of
multiple sessions of treatment that is not the first session of
treatment with the ICI, the biological sample is obtained from the
cancer patient at any time point between two consecutive sessions
of treatment, wherein said biological sample is simultaneously the
biological sample of step (i) and the reference biological sample
according to step (ii) for the next session assay according to step
(i). The time between two consecutive sessions of treatment may be
of 2 or 3 weeks, depending on the ICI, and the biological sample
may be obtained at day 1, 2, 3, 7, 14, or 21 days after the session
of treatment that is not the first session of treatment with the
ICI.
[0109] According to the invention, the fold-change established in
step (iii) is defined by a fold change of .gtoreq.1.5 indicating
upregulation or a fold change of .ltoreq.0.5 indicating
down-regulation in the level of each of the one or more of the
plurality of factors induced in the circulation of the cancer
patient in response to the treatment with the ICI, these values
being considered significant and predictive of a non-favorable or a
favorable response of the cancer patient to the treatment with said
ICI.
[0110] In accordance with the invention, the prediction of a
favorable or a non-favorable response of the cancer patient to the
treatment with the ICI is based on significant fold changes of one
or more, optionally two or more, three or more, four or more, five
or more, six or more, seven or more, eight or more, nine or more,
ten or more, eleven or more, twelve or more, thirteen or more,
fourteen or more, fifteen or more, twenty or more, or twenty-five
or more, of the induced factors. These factors induced in the
circulation of the cancer patient in response to treatment with the
ICI are molecular factors including cytokines, chemokines, growth
factors, enzymes and soluble receptors. These factors may be
pro-tumorigenic or pro-metastatic factors, and the pro-tumorigenic
factors may be pro-angiogenic, pro-inflammatory/chemotactic or
proliferative growth factors.
[0111] In certain embodiments, there is an increase (up-regulation)
of at least about 1.5-fold in the level of one or more of the
pro-tumorigenic or pro-metastatic factors, and the prediction is of
a non-favorable response of the cancer patient to the treatment
with the ICI. In certain embodiments, there is a decrease
(down-regulation) of at least about 0.5-fold in the level of one or
more of the pro-tumorigenic or pro-metastatic factors, and the
prediction is of a favorable response of the cancer patient to the
treatment with the ICI.
[0112] According to the method of the invention for treating a
cancer patient with an ICI, if the cancer patient has a
non-favorable response to the treatment with said ICI based on the
fold change established in (iii) for one or more of the plurality
of the induced factors, a selection of a dominant factor is made
among the one or more factors showing a fold change indicative of
said non-favorable response, and the patient is treated with the
same ICI in combination with an agent that blocks the dominant
factor.
[0113] The terms "block", "neutralize" or "inhibit" are herein used
interchangeably and refer to the capability of an agent of
preventing the factor from exerting its function/biological
activity.
[0114] As used herein, the term "dominant factor" denotes a potent
factor that may be upstream of a signaling pathway that affects a
biological process that is vital for the living cell and living
organism. These biological processes include proliferation,
inflammation, metastasis, and others, and are made of several
signaling pathways ultimately leading to activation or inhibition
of the biological process. A "signaling pathway" is a row of events
in which proteins in the same pathway transfer signal to each
other. After the first protein in a pathway receives a signal, it
activates another protein which activates another protein and so
forth, ultimately leading to activation of one or more cell
functions.
[0115] A "dominant factor" may also be a key factor that highly
interacts with, and highly affects, many other factors/proteins.
According to the invention, the dominant factors are selected based
on an algorithm which identifies the protein-protein interactions
of factors based on the literature. When a factor has more
interactions, it serves as a hub and therefore it is a dominant
factor. The term "protein-protein interactions" refers to physical
interactions or cross-talk between two or more proteins, resulting
in activation or inhibition of signal transduction or protein
activity. The term "protein hubs" refers to highly connected
proteins that play central and essential role in biological
processes and thus may confer the host with resistance, limit or
counteract the effectiveness of the treatment of the cancer patient
with the cancer therapy modality.
[0116] Examples of dominant factors include, without limitation,
Amphiregulin, EGF, EGFR, FGF, IFN-.gamma., IL-1.beta., IL-2, IL-6,
MMP-9, PDGF, TNF-.alpha. and VEGF-A.
[0117] To illustrate their qualifications as dominant factors, the
properties of some of these factors is provided herein.
Interleukin-1.beta.(IL-1.beta., IL-1b) is a cytokine member of the
IL-1 family, produced by different immune cells including
macrophages. It is a potent mediator of the inflammatory response
and also known to be involved in several biological processes such
as cell proliferation and apoptosis, as well as cell
differentiation. IL-1b was mostly investigated as a protein that
initiates the pro-inflammatory cascade. It physically interacts
with enzymes such as CASP1, IL1RA, IL1R1, CMA1, IL1RB, IL1A, IL1R2;
genetically interacts with MAPK8IP2, ZNF675 and UBEN2N; and is
co-expressed with A2M, CXCL8, IL18, CAASp1, IL1R1 and others. Thus,
IL-1b serves as a hub for interactions with a large number of
proteins that affect several biological pathways including cell
proliferation, apoptosis and differentiation as well as
inflammation and angiogenesis.
[0118] Another dominant factor is Interleukin-6 (IL-6), which is a
cytokine that acts mainly as a pro-inflammatory factor but also
sometimes as an anti-inflammatory factor produced by muscle cells
and as a result downregulate a number of pro-inflammatory proteins
such as IL-1, IL-10 and TNF-.alpha.. IL-6 is involved in a number
of biological processes including bone formation, disruption of
blood brain barrier, macrophage activation and innate immune system
contribution, stimulates the synthesis of neutrophils and B cells,
and is also involved in neurological activities such as disorders,
stress and depression. IL6 interacts and affects a large number of
proteins: it physically interacts with HRH1, OSM, IL6ST, IL6R and
ZBTB16, and was found to be co-expressed with a large number of
proteins such as PTPRE, CSF3, CCL2, CXCL8, CXCL3, ICAM1 SELE,
NFKBIZ among others. IL6 is involved in a number of pathways
mediated by proteins such as LRPPRC, OSM, PTPRE, PIAS1 and IL6R. As
such, IL6 serves as a dominant factor for a number of biological
processes involved in immune cell activity, cell genesis, and
cell-cell interactions.
[0119] A further dominant factor, vascular endothelial growth
factor A (VEGF-A), is a growth factor that stimulates the formation
of new blood vessels. It is involved in both angiogenesis
(endothelial cell proliferation) as well as vasculogenesis (bone
marrow-derived endothelial cell precursors and their
differentiation). VEGF is important for embryonic cell development
and neuronal development in the fetus, and is involved in leukocyte
proliferation and differentiation, inflammation and several
diseases such as age-related macular degeneration and the majority
of cancers. VEGF-A physically interacts with a large number of
proteins such as NRP1, NRP2, KDR, FLT1, PGF, THBS1, SPARC, GCP1 and
VEGFC; it is co-expressed with SEMA3F, SHB, THBS1, FLT1 and VEGFC;
it is involved with proteins of various pathways including PGF,
CD2AP, IQGAP1, NEDD4; and it affects a number of biological
processes such as angiogenesis, tumorigenesis, cell viability,
proliferation and differentiation. As such, VEGF-A is considered a
dominant factor, and vital factor for various biological processes
both in normal physiological conditions as well as in disease
states.
[0120] In certain embodiments, the selected dominant factor shows a
fold change of .gtoreq.1.5 indicative of a non-favorable response
of the cancer patient to the treatment with the ICI, and the
treatment of the patient with said ICI may proceed in combination
with an agent that blocks said dominant factor or the receptor
thereof.
[0121] In certain embodiments, the dominant factor is selected from
factors including amphiregulin, EGF, EGFR, FGF, IFN-.gamma.,
IL-1.beta., IL-2, IL-6, MMP9, PDGF, TNF-.alpha. and VEGF-A.
[0122] In certain embodiments, the dominant factor is MMP9, the ICI
is an anti-PD-1 or anti-PD-L1 monoclonal antibody, and the cancer
patient is treated with the ICI in combination with a MMP-9
inhibitor including SB-3CT.
[0123] In certain embodiments, the dominant factor is amphiregulin,
the ICI is an anti-PD-1 or anti-PD-L1 monoclonal antibody, and the
cancer patient is treated with the ICI in combination with an
anti-amphiregulin antibody.
[0124] The invention will now be illustrated by the following
non-limiting Examples.
EXAMPLES
Introduction
[0125] As discussed hereinbefore, recent clinical studies report
that patients may sometimes develop resistance to ICIs, or may not
respond to ICI therapy (Sharma et al., 2017). We describe herein
that the cancer patient, i.e., the host, generates pro-tumorigenic
factors in response to ICI therapy, which in turn contribute to
tumor re-growth, progression and resistance to therapy. In order to
identify the factors that contribute to this mechanism, we perform
our in vivo experiments in both non-tumor- and tumor-bearing
immunocompetent mice. This approach allows us to distinguish
between the therapeutic anti-tumor activity of ICIs and the effect
of these drugs on host cells. We focus on ICIs that are extensively
used in the clinic, including anti-PD1, anti-PD-L1 and anti-CTL-4
monoclonal antibodies, and use murine tumor models that are known
to be responsive or resistant to specific ICIs. For example, CT26
colon and EMT-6 breast carcinoma cell lines respond to anti-CTLA-4
and anti-PD-L1, respectively (Duraiswamy et al., 2013; Swart et a.,
2013), whereas MC38 colon and 4T1 breast carcinoma cell lines are
resistant or only modestly responsive to some ICIs (including
anti-PD-1) (De Henau et al., 2016; Kodumudi et al., 2016), as also
tested in our laboratory (not shown).
Materials and Methods
Materials
[0126] The following antibodies were purchased from BioXCell, West
Lebanon, N.H., USA: InVivoMAb anti-mouse-PD-1 (catalog #BEO146);
InVivoPlus anti-mouse-PD-L1 (catalog #BEO101); and InVivoMAb
Isotype control IgG2b antibody, (catalog #BE0090). SB-3CT (IUPAC
name: 2-(((4-phenoxyphenyl) sulfonyl)methyl)thiirane) was purchased
from MedKoo Biosciences Inc (catalog number 406563).
Anti-amphiregulin (catalog #AF989) was purchased from R&D
systems. A 10 mM stock solution of SB-3CT was prepared in 100% DMSO
(Sigma). For the in vivo experiment, the stock solution was diluted
to a final concentration of 1.25 mg/ml in 10% DMSO in normal
saline.
(i) Tumor cell culture: Murine EMT6 breast carcinoma cells were
purchased from the American Type Culture Collection (ATCC, USA).
The cells were passaged in culture for no more than 4 months after
being thawed from authentic stocks, and were regularly tested and
found to be mycoplasma-free (EZ-PCR mycoplasma test kit, Biological
Industries, Israel). Cells were cultured in Dulbecco's modified
eagle medium (DMEM) supplemented with 10% fetal bovine serum (FBS),
1% L-glutamine, 1% sodium-pyruvate and 1% penicillin-streptomycin
(Biological Industries, Israel). Cells were cultured at 37.degree.
C. in 5% CO.sub.2. (ii) Animal treatment protocols and tumor
models: Naive 8-10 week old female BALB/c, SCID or NOD-SCID mice
(Harlan, Israel) were intraperitoneally injected with anti-PD-1 or
irrelevant IgG rat-anti-mouse antibodies (BioXCell, West Lebanon,
N.H., USA). In other experiments, naive 8-10 week old female and
male BALB/c or C57bl/6 mice (Harlan, Israel) were intraperitoneally
injected with anti-PD-L1 or irrelevant IgG rat-anti-mouse
antibodies (BioXCell, West Lebanon, N.H., USA). In all cases,
antibodies were administered at a dose of 200 .mu.g/20 gr mouse,
every other day over the period of 1 week (3 injections in total).
EMT6 murine breast carcinoma cells (5.times.10.sup.5) were
implanted into the mammary fat pad of 8-10 week old BALB/c mice.
Tumor size was assessed regularly with Vernier calipers using the
formula width.sup.2.times.length.times.0.5. In some experiments,
mice were injected through the tail vein with EMT6 cells
(25.times.10.sup.3) to form experimental lung metastasis. Mouse
survival was monitored daily, and when mice faced difficulty
breathing or lost more than 15% of their body weight, they were
euthanized. Mice were sacrificed at endpoint and tumors were
processed as described below. (iii) Plasma samples and conditioned
medium preparation: Blood from control IgG-, anti-PD-1-, or
anti-PD-L1-treated mice was collected into EDTA-coated tubes by
cardiac puncture. Subsequently, plasma was isolated by
centrifugation of whole blood at 1000 g, 4.degree. C., for 20
minutes. Plasma was stored in aliquots at -80.degree. C. until
further use. Bone marrow derived cells were flushed from the femurs
of IgG or anti-PD-1 treated mice. Bone marrow cells
(1.times.10.sup.6 cells/ml) were cultured in serum-free DMEM for 24
hours to generate conditioned medium (CM). (iv) Modified Boyden
chamber assay: Serum-starved EMT6 cells (0.2.times.10.sup.5 cells)
were cultured in the upper compartment of the Boyden chamber that
was coated with either 50 .mu.l Matrigel (BD Biosciences, Bedford,
Mass.) for invasion assays or 100 .mu.l fibronectin (10 .mu.g/ml)
for migration assays. The lower compartment was filled with DMEM
medium containing 5% plasma obtained from IgG-treated or anti-PD-1
treated BALB/c, SCID or NOD-SCID mice. After 4 hours (for
migration) or overnight (for invasion) incubation, the cells that
migrated to the bottom filter, were fixed and stained with Crystal
violet. Images were captured using a LEICA DMI 6000B fluorescence
inverted microscope per .times.100 objective-field (Leica
Microsystems, Germany). At least 10 fields per group were
evaluated. The percentage of positive pixels (representing cells)
covering the bottom membrane compartment over the total pixels in
the field was calculated using Photoshop SC2 V9.0 (San Jose,
Calif., USA). Experiments were carried out in triplicate, and were
independently performed at least twice. (v) Matrigel plug assay:
Matrigel (0.5 ml, BD Biosciences, USA) was mixed with plasma
obtained from IgG-treated or anti-PD-1-treated mice (at a ratio of
10:1, Matrigel:plasma, by volume). The Matrigel was injected
subcutaneously into the flanks of BALB/c female mice, 7-8 weeks of
age. Plugs were removed 10 days later, and were subsequently
prepared as a single cell suspension for flow cytometric analysis
or processed for histological analysis as described below. (vi)
Flow cytometry analysis: Matrigel plugs, tumors or spleens were
harvested from mice and prepared as single cell suspensions. Bone
marrow derived cells (BMDCs) were flushed from femurs. Blood was
drawn by retro-orbital sinus bleed. In all cases, cells were
immunostained with antibody mixtures to identify different cell
types according to the following markers: Myeloid derived
suppressor cells (MDSCs), CD11b+/Gr-1+/Ly6G+/Ly6C+; M1 macrophages,
CD11c+/CD206-/F4/80+; M2 macrophages, CD11c-/CD206+/F4/80+;
cytotoxic T lymphocytes (CTLs), CD8+/CD25+; T helper cells, CD4+;
and T regulatory cells, CD4+/CD25+/FOXp3+. All monoclonal
antibodies were purchased from Biolegend, BD Biosciences, or
R&D systems and used in accordance with the manufacturers'
instructions. At least 100,000 events were acquired using a Cyan
ADP flow cytometer and analyzed with Summit v4.3 software (Beckman
Coulter). (vii) Immunohistochemistry: Matrigel plugs were stored in
optimum cutting temperature (OCT) at -80.degree. C., and
cryosectioned (10 .mu.m). Matrigel plug sections were stained with
H&E (Emmonya Biotech Ltd, Bulgaria) to evaluate the
colonization of host cells. Endothelial cells in Matrigel sections
were detected by immunostaining using a CD31 antibody (1:100, BD
Biosciences) and a Cy3-conjugated secondary antibody (1:200,
Jackson ImmunoResearch). Images were captured using the Leica CTR
6000 system. (viii) Antibody arrays: Three protein profiling
experiments were performed. In the first experiment, plasma samples
extracted from IgG- or anti-PD-1 treated female BALB/c mice were
pooled per treatment group (n=5 per group). Samples were applied to
a membrane-based Proteome Profiler Mouse XL Cytokine Array (R&D
Systems; Cat no: ARY028) according to the manufacturer's
instruction to screen a total of 111 factors. In the second
experiment, plasma samples extracted from IgG- or anti-PD-L1
treated female or male BALB/c or C57b1/6 mice were pooled per group
(n=7 per group). Samples were applied to a glass slide-based
Quantibody Mouse Cytokine Array (RayBiotech, Cat no: QAM-CAA-4000)
according to the manufacturer's instruction to screen a total of
200 factors. In the third experiment, plasma samples extracted from
IgG- or anti-PD-1 treated female BALB/c or SCID mice were pooled
per group (n=7 per group). Samples were applied to a glass
slide-based Quantibody Mouse Cytokine Array (RayBiotech, Cat no:
QAM-CAA-4000) according to the manufacturer's instruction to screen
a total of 200 factors. For the membrane-based array, pixel
densities on developed X-ray films were analyzed using transmission
mode densitometer and image analysis software. For the glass
slide-based arrays, the fluorescent readout was detected by a laser
fluorescent scanner. In all cases, data was normalized and the fold
changes for each factor on the arrays were determined by
calculating the ratio of treated: control values. (ix) Statistical
analysis: Data are expressed as mean.+-.standard deviation (SD).
The statistical significance of differences was assessed by one-way
ANOVA, followed by Tukey ad hoc statistical test using GraphPad
Prism 5 software (La Jolla, Calif.). Student t-test was used in
some experiments when comparing only two groups. Differences
between all groups were compared with each other. For tumor growth
experiments, statistical significance is assessed by multiple
t-test. For survival analysis, differences are assessed by Log-rank
Mantle-Cox. Differences were considered significant at p values
below 0.05.
Example 1. In Vitro Assessment of Tumor Cell Aggressiveness in
Response to Anti-PD-1 Treatment
[0127] To test whether anti-PD-1 treatment induces a response in
the host which in turn has a direct effect on tumor cell
aggressiveness, in vitro migration and invasion assays were
performed in the presence of plasma extracted from healthy naive
mice treated with anti-PD-1 or IgG control antibodies. The use of
naive mice allowed us to evaluate host-mediated effects,
independent of tumor presence. To this end, non-tumor bearing
Balb/c mice were intraperitoneally injected with anti-PD-1 or IgG
control antibodies over a period of 1 week (3 injections in total).
Mice were sacrificed, blood was drawn, and plasma was purified. The
effect of the plasma samples on invasive and migratory properties
of EMT6 tumor cells was assessed in vitro using a modified Boyden
chamber assay. FIGS. 1A-B demonstrate that plasma from
anti-PD-1-treated mice significantly enhances the invasive and
migratory properties of EMT6 cells in comparison to plasma from
IgG-treated control mice. These findings suggest that host-derived
factors in the plasma of anti-PD-1-treated mice potentiate tumor
cell aggressiveness. Since metalloproteinases (MMPs) are known to
support tumor cell invasion and migration, we next evaluated the
expression level of MMPs in conditioned medium (CM) of bone marrow
derived cells (BMDCs) obtained from mice treated with anti-PD-1 or
IgG control antibodies. We found that MMP9 was highly elevated in
the CM of BMDCs obtained from mice treated with anti-PD-1
antibodies compared to control (FIGS. 1C-D). Collectively, these
results suggest that, in response to anti-PD-1 treatment, host
cells secrete factors into the circulation which support tumor cell
aggressiveness.
Example 2. Cells of the Adaptive Immune System Secrete
Tumor-Supporting Factors in Response to Anti-PD-1 Treatment
[0128] To identify the host cell types that secrete
tumor-supporting factors in response to anti-PD-1 treatment,
similar experiments to those described in Example 1 were performed.
However, in this case, SCID CB17 mice, which lack adaptive immune
cells, and NOD-SCID mice, which are deficient in adaptive immune
cell types and dysfunctional in innate immune cell types, were
used. Non-tumor bearing SCID or NOD-SCID mice were
intraperitoneally injected with anti-PD-1 or IgG control antibodies
over a period of 1 week (3 injections in total). Mice were
sacrificed, blood was drawn, and plasma was purified. The effect of
the plasma samples on invasive and migratory properties of EMT6
tumor cells was assessed in vitro using a modified Boyden chamber
assay. Our results demonstrate that plasma from anti-PD-1-treated
SCID mice inhibited the invasive properties of EMT6 cells, whereas
plasma from NOD-SCID mice had no effect on invasion and inhibited
migration of EMT6 cells in comparison to controls (FIG. 2, FIGS.
3A-B). We next evaluated the expression level of MMP9 in
conditioned medium (CM) of bone marrow derived cells (BMDCs)
obtained from NOD-SCID mice treated with anti-PD-1 or IgG control
antibodies. As shown in FIGS. 3C-D, the levels of MMP9 were similar
in CM from bone marrow cells extracted from anti-PD-1-treated and
control mice. These collective results are in clear contrast to
those described in Example 1 and shown in FIG. 1. They suggest that
factors promoting tumor cell invasion and migration are secreted
primarily by cells of the adaptive immune system in response to
anti-PD-1 treatment.
Example 3. In Vivo Assessment of Tumor Progression in Response to
Anti-PD-1 Treatment
[0129] To evaluate how the response of the host to anti-PD-1
treatment affects tumor fate, we studied the in vivo metastatic
properties of tumor cells which had been pre-treated with plasma
derived from anti-PD-1-treated naive (non-tumor bearing) mice. To
this end, EMT6 cells were pre-cultured for 4 hours in serum-free
medium containing 10% plasma which was extracted from naive BALB/c
mice treated with anti-PD-1 antibodies or control IgG. The cells
were washed and subsequently injected intravenously to the tail
vein of naive BALB/c mice to generate an experimental pulmonary
metastasis model. The results in FIG. 4 demonstrate that mice
injected with EMT6 cells which had been pre-exposed to plasma from
anti-PD-1-treated mice exhibit an increased mortality rate in
comparison to control mice injected with EMT6 cells pre-treated
with plasma from IgG-treated mice. The lungs from all mice were
removed and evaluated for metastasis. No significant differences
were observed in the number of metastatic lesions in the lungs
(data not shown).
Example 4. Anti-PD-1 Treatment Promotes the Colonization of
Tumor-Supporting Host Cells in Matrigel Plugs
[0130] To characterize the effect of anti-PD-1 treatment on the
host cell composition in the tumor microenvironment, a Matrigel
plug assay was used. Matrigel is a material composed of tumor
extracellular matrix found in the tumor microenvironment. The
Matrigel was mixed in a 10:1 ratio with plasma from
anti-PD-1-treated or IgG-treated mice. Subsequently, the
Matrigel-plasma mixture was implanted into flanks of naive BALB/c
mice, and plugs were formed. After 10 days, plugs were removed,
sectioned and immunostained for endothelial cells. As shown in FIG.
5A, blood vessels were more abundant in Matrigel plugs containing
plasma from anti-PD-1-treated mice in comparison to the control.
This suggests that host-derived, anti-PD-1-induced circulating
factors promote angiogenesis. In a parallel experiment, Matrigel
plugs were prepared as single cell suspensions and analyzed by flow
cytometry to identify various immune cell types. As shown in FIG.
5B and Table 1, the levels of activated cytotoxic T lymphocytes
(CTLs) and activated T helper cells were increased in Matrigel
plugs containing plasma from anti-PD-1-treated mice in comparison
to the control, in line with the therapeutic benefit of
immunotherapy. However, the levels of other cell types associated
with pro-tumorigenic activity including M2-like macrophages and
MDSCs were also increased. These findings suggest that anti-PD-1
treatment induces a host response that involves tumor-supporting
immune cells.
[0131] The results of the Matrigel assay prompted us to
characterize the changes in immune cell composition in tumors and
different organs in response to anti-PD-1 treatment. To this end,
naive non-tumor bearing BALB/c mice or BALB/c mice bearing EMT6
tumors (whose tumors had reached a size of 500 mm.sup.3) were
intraperitoneally injected with anti-PD-1 or IgG antibodies over
the period of 1 week (3 injections in total). Mice were sacrificed
and blood, spleens, BMDCs and tumors were extracted and analyzed by
flow cytometry to identify different immune cell types. The data
shown in Table 1 shows that within the tumor, as expected, CTLs
were highly elevated and active, in line with the therapeutic
benefit of immunotherapy. However, the levels of adaptive immune
cells, including T helper and CTLs, were reduced in the blood and
BMDCs of both non-tumor and tumor bearing anti-PD-1 treated mice in
comparison to controls. In addition, in hematopoietic organs (e.g.,
spleen and BMDCs) of non-tumor or tumor bearing mice, the levels of
innate immune cells, including M1 and M2 macrophages as well as
MDSCs, fluctuated and sometimes increased. These results indicate
that while in tumors, as expected, CTLs are active and promote
anti-tumor activity, in other evaluated organs, tumor-supporting
immune cells including M2 macrophages and MDSCs are elevated in
response to anti-PD-1 treatment, and therefore may counteract the
anti-tumor activity of CTLs.
Example 5. The Effect of Immune Checkpoint Inhibitor Therapy on
Circulating Host-Derived Factors--a Protein Profiling Approach in
Mice
[0132] The data presented in FIGS. 1-5 suggest that anti-PD-1
therapy induces an upregulation of factors in the circulation which
ultimately promotes tumor cell aggressiveness. Such effects may
occur in response to other types of immune checkpoint inhibitor
therapies. To identify host-derived circulating factors whose
levels change in response to anti-PD-1 and anti-PD-L1 therapies, we
performed 3 protein array-based screens using naive (non-tumor
bearing) mice. The use of naive mice allows us to identify factors
specifically generated by the host in response to therapy,
independent of the tumor.
[0133] In the first screen, naive 8-10 week old female BALB/c mice
(n=3) were intraperitoneally injected with anti-PD-1 rat anti-mouse
antibody (BioXCell, West Lebanon, N.H., USA) at a dose of 200
.mu.g/20 gr mouse every other day over a period of 1 week (3
injections in total). Control mice (n=3) were similarly injected
with a rat-anti-mouse IgG antibody at the same dose. One week after
the first injection, mice were sacrificed, and blood was collected
into EDTA-coated tubes by cardiac puncture. Plasma was isolated by
centrifugation of whole blood at 1300 g for 10 minutes at room
temperature. Supernatants (representing the plasma samples) were
collected and pooled per group. Aliquots were stored at -80.degree.
C. until further use. Plasma samples were applied to a
membrane-based Proteome Profiler Mouse XL Cytokine Array (R&D
Systems; Cat no: ARY028) to screen a total of 111 factors. A full
list of cytokines, enzymes and growth factors detected by the array
is shown in Table 2. Pixel densities on developed X-ray films were
analyzed using transmission mode densitometer and image analysis
software. Normalized data was analyzed to identify factors whose
circulating levels were changed in response to anti-PD-1 treatment.
Specifically, the fold change was determined for each factor by
calculating the ratio of treatment: control values. Factors
exhibiting a fold change of more than 1.5 or less than 0.5 were
defined as being up- or down-regulated, respectively, in response
to anti-PD-1 treatment. These factors and their respective fold
changes are listed in Table 3. Many of the factors that were
upregulated in response to anti-PD-1 treatment are key players in
pro-tumorigenic and pro-metastatic processes such as angiogenesis,
inflammation, chemotaxis and proliferation. Upregulated
pro-angiogenic factors include: G-CSF; GM-CSF; and PDGF-BB.
Up-regulated pro-inflammatory and/or chemotactic factors include:
CCL17/TARC; CCL5/RANTES; G-CSF; GM-CSF; IFN-gamma; IL-1Ralpha;
IL-2; IL-6; IL-7; IL-10; IL-12p40; IL-13; IL-33; and M-CSF.
Upregulated proliferative growth factors include: FGF-21; Gas6; and
HGF. Upregulated pro-metastatic factors include: MMP-9.
[0134] In the second screen, naive 8-10 week old female BALB/c,
male BALB/c, female C57Bl/6 or male C57Bl/6 mice (n=7 mice per
group) were intra-peritoneally injected with anti-PD-L1 or control
IgG antibodies (BioXCell, West Lebanon, N.H., USA) every other day
over a period of 1 week (3 injections in total) at a dose of 200
.mu.g/20 gr mouse per injection. Twenty-four hours after the last
administration, mice were sacrificed, blood was drawn and plasma
was prepared. Plasma samples from each group were pooled and
applied to a glass slide-based Quantibody Mouse Cytokine Array
(RayBiotech, Cat no: QAM-CAA-4000) according to the manufacturer's
instruction to screen a total of 200 factors. A full list of
cytokines, enzymes and growth factors detected by the array is
shown in Table 4. The fold changes were determined for each factor
on the protein array by calculating the ratio of treated: control
values. Factors exhibiting a fold change of more than 1.5 or less
than 0.5 were defined as being up- or down-regulated, respectively,
in response to anti-PD-L1 treatment. These factors, and their
respective fold changes are listed in Table 5. The data demonstrate
that the profiles of up- and down-regulated factors do not
completely overlap when comparing between the different mouse
strains or when comparing between males and females of the same
strain. This suggests that the response to anti-PD-L1 treatment is
genotype-dependent. This may reflect differences known to exist
also among cancer patients, and therefore provides a rationale for
testing the response of the host in patients in a personalized
manner. Many of the factors that were upregulated in response to
anti-PD-L1 treatment are key players in pro-tumorigenic and
pro-metastatic processes such as inflammation, chemotaxis and
proliferation. Upregulated pro-angiogenic factors include: G-CSF;
and SCF. Upregulated pro-inflammatory and/or chemotactic factors
include: Eotaxin-2; G-CSF; IL-1ra; IL-6; IL-7; IL-33; I-TAC;
MadCAM-1; MCP-5; SCF; and TACI. Upregulated proliferative growth
factors include: amphiregulin; Axl; EGF; and HGF. Upregulated
pro-metastatic factors include: ADAMTS1 and pro-MMP9.
[0135] To gain insight into which host cell types secrete these
pro-tumorigenic factors, we performed a similar screen, comparing
between BALB/c and SCID mice treated with anti-PD-1 or control IgG
antibodies. SCID mice carry the severe combined immune deficiency
(SCID) mutation on the BALB/c background, and therefore lack
functional adaptive immune cell types (B cells and T cells). Naive
8-10 week old female BALB/c or SCID mice (n=7 mice per group) were
intraperitoneally injected with anti-PD-1 or control IgG antibodies
(BioXCell, West Lebanon, N.H., USA) every other day over a period
of 1 week (3 injections in total) at a dose of 200 .mu.g/20 gr
mouse per injection. Twenty-four hours after the last
administration, mice were sacrificed, blood was drawn and plasma
was prepared. Plasma samples from each group were pooled and
applied to a glass slide-based Quantibody Mouse Cytokine Array
(RayBiotech, Cat no: QAM-CAA-4000) according to the manufacturer's
instruction to screen a total of 200 factors. A full list of
cytokines, enzymes and growth factors detected by the array is
shown in Table 4. The fold changes were determined for each factor
on the protein array by calculating the ratio of treated: control
values. Factors exhibiting a fold change of more than 1.5 or less
than 0.5 were defined as being up- or down-regulated, respectively,
in response to anti-PD-1 treatment. These factors, and their
respective fold changes are listed in Table 6. Several factors were
found to be up-regulated in response to anti-PD-1 treatment, some
of which were specific to BALB/c and not SCID mice, e.g., ADAMTS1;
amphiregulin, I-TAC and SCF. These results suggest that these
specific factors are secreted by cells of the adaptive immune
system in response to anti-PD-1 treatment.
[0136] Collectively, these results demonstrate that anti-PD-1 and
anti-PD-L1 treatments induce a response in the host that supports
tumor progression, counteracting the desired therapeutic effects of
immune checkpoint inhibitor therapy.
Example 6. The Effect of Reducing Host-Derived MMP-9 Levels on ICI
Therapy in a Primary Breast Tumor Model
[0137] Matrix metallopeptidase 9 (MMP9) is an enzyme that belongs
to the zinc-metalloproteinases family involved in the degradation
of the extracellular matrix. MMP-9 was found to be induced in
BALB/c mice following treatment with anti-PD-1 or anti-PD-L1, as
shown in Examples 1 and 5 above, which demonstrate that: i) MMP-9
is secreted by bone marrow-derived cells of naive BALB/c mice in
response to anti-PD-1 treatment (FIG. 1C-D); ii) the plasma level
of MMP9 is increased 5.4 fold in response to anti-PD-1 treatment in
naive BALB/c mice (Table 3); iii) the_plasma level of pro-MMP-9 is
increased 2-3 fold in response to anti-PD-L1 treatment in naive
BALB/c mice (Table 5).
[0138] To investigate whether inhibiting host-derived MMP9 improves
the efficacy of anti-PD-1 or anti-PD-L1 therapy, the MMP2/MMP9
selective inhibitor SB-3CT is used in combination with anti-PD-1 or
anti-PD-L1 antibodies. EMT6 murine breast carcinoma cells
(5.times.10.sup.5) are orthotopically implanted in the mammary fat
pad of female BALB/c mice, age 8-weeks, (Harlan, Israel). Tumor
size is assessed regularly with Vernier calipers using the formula
width.sup.2.times.length.times.0.5. When tumors reach a size of 100
mm.sup.3, mice are randomly assigned to the following treatment
groups (n=6 mice per group): i) control; ii) anti-PD-1 monotherapy;
iii) anti-PD-L1 monotherapy; iv) MMP2/MMP9 selective inhibitor
SB-3CT monotherapy; v) anti-PD-1 and SB-3CT combination therapy;
and vi) anti-PD-L1 and SB-3CT combination therapy. Anti-PD-1,
anti-PD-L1 and IgG control antibodies are administered by
intraperitoneal injections at a dose of 200 .mu.g/20 g mouse every
3 days. SB-3CT is administered by intraperitoneal injections at a
dose of 1 mg/20 g mouse every 3 days. Control mice are injected
with IgG antibody and vehicle (10% DMSO in normal saline). Mice
receiving either anti-PD-1 or anti-PD-L1 monotherapies are also
injected with vehicle (10% DMSO in normal saline). Mice receiving
SB3-CT monotherapy are also injected with IgG control antibodies.
Tumor growth and mouse survival are monitored. At endpoint (when
tumors reach a size of .about.1500 mm.sup.3), mice are
sacrificed.
[0139] It is expected that treatment of BALB/c mice, which exhibit
induced MMP9 in response to treatment with anti-PD1 or anti-PD-L1,
with the combination of SB-3CT and either anti-PD-1 or anti-PD-L1
will be more effective in reducing tumor size and increasing
survival than monotherapy with anti-PD-1 or anti-PD-L1 without the
MMP9 inhibitor.
Example 7. The Effect of Reducing Host-Derived Amphiregulin Levels
on ICI Therapy in a Primary Breast Tumor Model
[0140] Amphiregulin is one of the ligands of the epidermal growth
factor receptor (EGFR). Studies have demonstrated a functional role
of amphiregulin in several aspects of tumorigenesis. Amphiregulin
was chosen in light of our findings described in Example 5 above,
which demonstrate that the plasma levels of amphiregulin are
increased 2-3 fold in response to anti-PD-L1 treatment in naive
BALB/c and C57/bl/6 mice (Table 5), and 3.7 fold in response to
anti-PD-1 treatment in BALB/c mice (Table 6).
[0141] To investigate whether inhibiting host-derived amphiregulin
(which is upregulated in BALB/c mice in response to either
anti-PD-1 or anti-PD-L1 treatment) improves the efficacy of
anti-PD-1 or anti-PD-L1 therapy, the anti-mouse amphiregulin
antibody AF989 is used in combination with anti-PD-1 or anti-PD-L1
antibodies. 5.times.10.sup.5 EMT6 murine breast carcinoma cells are
orthotopically implanted in the mammary fat pad of BALB/c mice.
When tumors reach a size of 100 mm.sup.3, mice are randomly
assigned to the following treatment groups: i) control; ii)
anti-PD-1 monotherapy; iii) anti-PD-L1 monotherapy; iv) monotherapy
with anti-mouse amphiregulin antibody AF989; v) anti-PD-1 and AF989
combination therapy; and vi) anti-PD-L1 and AF989 combination
therapy. Control mice are injected with IgG antibody. Anti-PD-1,
anti-PD-L1 and IgG control antibodies are administered by
intraperitoneal injections at a dose of 200 .mu.g/20 g mouse every
3 days. Anti-amphiregulin antibody AF989 is administered by
intraperitoneal injection at a dose of 10 .mu.g/20 g mouse every 3
days. Tumor growth and mouse survival are monitored.
[0142] It is expected that treatment of BALB/c mice, which exhibit
induced amphiregulin expression in response to treatment with
anti-PD1 or anti-PD-L1, with a combination of AF989 antibody and
either anti-PD-1 or anti-PD-L1 will be more effective in reducing
tumor size and increasing survival than monotherapy with anti-PD-1
or anti-PD-L1 without the anti-amphiregulin antibody.
APPENDIX
TABLE-US-00001 [0143] TABLE 1 Changes in immune cell compositions
from 3 experimental settings comparing anti-PD-1-treatment relative
to control Active MDSCs Active Active B T NK NK Gr1+/ Organ Th CTLs
cells reg cells cells Macrophages CD11b+ Naive Blood .dwnarw.
.dwnarw. .dwnarw. .dwnarw. .uparw. -- .dwnarw. -- mice Spleen --
.dwnarw. .uparw. .dwnarw. -- .uparw. M1.uparw. -- M2.dwnarw. BM --
.dwnarw. .uparw. -- .dwnarw. .dwnarw. M1.uparw. .dwnarw. M2.dwnarw.
Tumor Tumor .uparw. .uparw.* -- .dwnarw.* M1.uparw.*
Ly6C.sup.+/Ly6G.sup.- bearing M2.uparw. .dwnarw. mice
Ly6C.sup.-/Ly6G.sup.+ .dwnarw.* Blood -- -- .dwnarw. .dwnarw.* --
-- -- Ly6C.sup.+/Ly6G.sup.- .dwnarw.* Ly6C.sup.-/Ly6G.sup.+
.dwnarw. Spleen .uparw. .uparw.* .uparw. .uparw. .uparw. .uparw.*
M1.dwnarw. Ly6C.sup.+/Ly6G.sup.- M2.uparw. .dwnarw.*
Ly6C.sup.-/Ly6G.sup.+ .uparw.* BM .dwnarw.* .dwnarw. .dwnarw. --
.dwnarw. .dwnarw. M1.dwnarw. Ly6C.sup.+/Ly6G.sup.- M2.uparw.
.uparw. Ly6C.sup.-/Ly6G.sup.+ .dwnarw. Matrigel .uparw.* .uparw.*
-- .uparw. .uparw. .uparw.* M1.uparw. Ly6C.sup.+/Ly6G.sup.- Plug
M2.uparw. .uparw.* assay Ly6C.sup.-/Ly6G.sup.+ .uparw.* *p <
0.05
TABLE-US-00002 TABLE 2 List of 111 factors participating in the
antibody array screen performed with plasma from mice receiving
immune-checkpoint inhibitor anti-PD-1 therapy Proteome Profiler
Mouse XL Cytokine Array (R&D Systems; Cat no: ARY028)
Adiponectin/Acrp30 CXCL9/MIG IL-2 PDGF-BB Amphiregulin CXCL10/IP-10
IL-3 Pentraxin 2/SAP Angiopoietin-1 CXCL11/I-TAC IL-4 Pentraxin
3/TSG-14 Angiopoietin-2 CXCL13/BLC/BCA-1 IL-5 Periostin/OSF-2
Angiopoietin-like 3 CXCL16 IL-6 Pref-1/DLK-1/FA1 BAFF/BLyS/TNFS
F13B Cystatin C IL-7 Proliferin C1q R1/CD93 Dkk-1 IL-10 Proprotein
Convertase 9/PCSK9 CCL2/JE/MCP-1 DPPIV/CD26 IL-11 RAGE CCL3/CCL4
MIP-1 EGF IL-12p40 RBP4 alpha/beta CCL5/RANTES Endoglin/CD105 IE-13
Reg3G CCL6/C10 Endostatin IE-15 Resistin CCL11/Eotaxin Fetuin
A/AHSG IL-17A E-Selectin/CD62E CCL12/MCP-5 FGF acidic IL-22
P-Selectin/CD62P CCL17/TARC FGF-21 IL-23 Serpin E1/PAI-1
CCL19/MIP-3 beta Flt-3 Ligand IL-27 Serpin F1/PEDF CCL20/MIP-3
alpha Gas6 IL-28 Thrombopoietin CCL21/6Ckine G-CSF IL-33
TIM-1/KIM-1/HAVCR CCL22/MDC GDF-15 LDL R TNF-alpha CD14 GM-CSF
Leptin VCAM-1/CD106 CD40/TNFRSF5 HGF LIF VEGF CD160 ICAM-1/CD54
Lipocalin-2/NGAL WISP-1/CCN4 Chemerin IFN-gamma LIX Chitinase
3-like 1 IGFBP-1 M-CSF Coagulation Factor IGFBP-2 MMP-2 III/Tissue
Factor Complement IGFBP-3 MMP-3 Component C5/C5a Complement Factor
D IGFBP-5 MMP-9 C-Reactive Protein/CRP IGFBP-6 Myeloperoxidase
CX3CL1/Fractalkine IL-1 alpha/IL1F1 Osteopontin (OPN) CXCL1/KC IL-1
beta/IL-1F2 Osteoprotegerin/ TNFRSF11B CXCL2/MIP-2 IL-1ra/IL-1F3
PD-ECGF/Thymidine phosphorylase
TABLE-US-00003 TABLE 3 Summary of fold changes in the levels of
circulating factors in anti-PD1-treated vs control BALB/c mice Fold
change (anti-PD-1 vs IgG) C14 8.0 CCL17/TARC 5.0 CCL19/MIP-3.beta.
1.5 CCL21/6Ckine 1.7 CCL3/CCL4/MIP-1.alpha./.beta. 1.8 CCL5/RANTES
13.0 CD40/TNFRSF5 3.3 Chemerin 3.6 Chitinase 3-like 1 2.6
CXCL13/BCL/BCA-1 1.8 CXCL9/MIG 1.7 Cystatin C 21.2 DKK-1 5.2
Endoglin/CD105 2.8 E-Selectin/CD62E 1.6 Fetuin A/AHSG 14.6 FGF
acidic 1.7 FGF-21 2.5 Gas 6 2.1 G-CSF 2.9 GM-CSF 2.2 HGF 3.9
IFN-.gamma. 1.9 IL-10 7.2 IL-12 p40 23.5 IL-13 2.5
IL-1r.alpha./IL-1F3 3.1 IL-2 5.5 IL-22 2.4 IL-27 p28 2.3 IL-28A/B
2.0 IL-33 3.0 IL-4 1.5 IL-6 15.6 IL-7 5.2 LDL R 8.1 Leptin 2.0 LIF
1.8 Lipocalin-2/NGAL 4.8 M-CSF 6.9 MMP-9 5.4 Myeloperoxidase 6.7
Osteprotegerin/TNFRS11B 1.8 PDGF-BB 4.1 Pentraxin 2/SAP 2.7
Pentraxin 3/TSG-14 3.3 Periostin/TSG-14 2.0 Pref-1/DLK-1/FA1 5.8
Proliferin 5.8 RBP4 4.5 Serpin E1/PAI-1 3.8 Serpin F1/PAI-1 1.6
TIM-1/KIM-1/HAVCR 1.7 TNF-.alpha. 4.3 VCAM-1/CD106 1.6 VEGF 0.3
WISP-1/CCN4 3.0
TABLE-US-00004 TABLE 4 List of 200 factors participating in the
antibody array screen performed with plasma from mice receiving
immune-checkpoint inhibitor (anti-PD-1 or anti-PD-L1) therapy
Quantibody Mouse Cytokine Array (RayBiotech; Cat no: QAM-CAA-4000)
4-1BB (TNFRSF9/CD137); 6Ckine (CCL21); ACE; Activin A; ADAMTS1
(METH1); Adiponectin; ALK-1; Amphiregulin; ANG-3; ANGPTL3; Artemin;
Axl; B7-1; BAFF R; bFGF; BLC (CXCL13); BTC; C5a; CCL28; CCL6; CD27;
CD27L; CD30; CD30L; CD36; CD40; CD40L; CD48; CD6; Chemerin;
Chordin; Clusterin; CRP; Cardiotrophin-1; CTLA4; CXCL16; Cystatin
C; DAN; Decorin; Dkk-1; DLL4; Dtk; E-Cadherin; EDAR; EGF; Endocan;
Endoglin; Eotaxin (CCL11); Eotaxin-2 (CCL24); Epigen; Epiregulin;
E-selectin; Fas; Fas L; Fcg RIIB; Fetuin A; Flt-3L; Fractalkine;
Galectin-1; Galectin-3; Galectin-7; Gas 1; Gas 6; G-CSF; GITR; GITR
L; GM-CSF; gp130; Granzyme B; Gremlin; H60; HAI-1; HGF; HGF R;
ICAM-1; INFg; IFNg R1; IGF-1; IGFBP-2; IGFBP-3; IGFBP-5; IGFBP-6;
IL-1 R4; IL-10; IL- 12p40; IL-12p70; IL-13; IL-15; IL-17; IL-17B;
IL-17B R; IL-17E; IL-17F; IL-1a; IL- 1b; IL-1ra; IL-2; IL-2 Ra;
IL-20; IL-21; IL-22; IL-23; IL-28; IL-3; IL-3 Rb; IL-33; IL-4;
IL-5; IL-6; IL-7; IL-7 Ra; IL-9; I-TAC (CXCL11); JAM-A; KC (CXCL1);
Kremen-1; Leptin; Leptin R; Limitin; Lipocalin-2; LIX; LOX-1;
L-selectin; Lungkine; Lymphotactin; MadCAM-1; Marapsin; MBL-2;
MCP-1 (CCL2); MCP-5; MCSF; MDC (CCL22); Meteorin; MFG-E8; MIG
(CXCL9); MIP-1a (CCL3); MIP- 1b (CCL4); MIP-1g; MIP-2; MIP-3a
(CCL20); MIP-3b (CCL19); MMP-10; MMP-2; MMP-3; Neprilysin; Nope;
NOV; OPG; OPN; Osteoactivin; OX40 Ligand; P- Cadherin; PDGF-AA;
Pentraxin 3; Periostin; Persephin; PF4 (CXCL4); PlGF-2;
Progranulin; Prolactin; Pro-MMP-9; Prostasin; P-selectin; RAGE;
RANTES (CCL5); Renin 1; Resistin; SCF; SDF-1a; sFRP-3; Shh-N; SLAM;
TACI; TARC (CCL17); TCA-3; TCK-1 (CXCL7); TECK (CCL25); Testican 3;
TGFb1; TIM-1; TNF RI; TNF RII; TNFa; TPO; TRAIL; TRANCE; TREM-1;
TREML1; TROY; Tryptase epsilon; TSLP; TWEAK; TWEAK R; VACM-1; VEGF;
VEGF R1; VEGF R2; VEGF R3; VEGF-B; VEGF-D
TABLE-US-00005 TABLE 5 Summary of fold changes in the levels of
circulating factors in anti-PD-L1-treated vs control BALB/c and
C57bl/6 mice Fold change (anti-PD-L1 vs IgG) BALB/c C57bl/6 Female
Male Female Male ADAMTS1 1.6 0.5 2.1 1.9 ALK-1 2.3 1.5 6.0 0.6
Amphiregulin 2.7 2.8 3.0 0.9 Axl 2.7 2.2 2.3 1.9 CD30 2.4 2.3 1.5
1.5 Dkk-1 1.5 0.8 1.4 0.4 EGF 6.3 4.1 0.7 4.0 Eotaxin-2 1.8 1.7 1.0
0.8 Epiregulin 2.7 0.6 0.4 0.2 Fcg RIIB 2.3 1.5 1.4 0.9 Fractalkine
2.7 2.0 1.0 1.0 G-CSF 2.2 2.7 2.0 1.2 GITR L 8.2 7.4 1.4 0.3
Granzyme B 2.0 1.1 2.7 0.7 HGF 2.3 0.6 3.7 3.6 HGF R 10.4 1.7 24.9
2.4 IL-1ra 3.6 1.8 2.9 1.3 IL-33 1.3 2.2 1.6 1.0 IL-6 1.8 1.7 1.0
0.5 IL-7 1.7 1.6 1.1 0.0 I-TAC 6.1 7.4 4.2 1.1 Lipocalin-2 2.0 4.8
2.6 2.1 MadCAM-1 0.8 7.1 2.6 2.4 MCP-5 2.2 4.5 1.3 1.2 MDC 2.2 1.8
0.9 0.6 Meteorin 0.6 0.7 1.9 3.0 MFG-E8 1.8 2.6 4.3 1.8 MIG 1.6 1.2
1.9 1.4 MIP-3b 1.5 2.8 1.7 0.9 OPG 0.8 0.9 1.7 2.2 Osteoactivin 0.8
1.2 2.5 2.4 P-Cadherin 0.8 0.9 1.7 2.1 Pentraxin 3 1.3 1.6 3.0 2.7
Pro-MMP-9 3.0 2.2 1.1 1.3 SCF 2.6 3.3 4.5 3.4 TACI 2.7 2.9 2.3 1.3
TARC 1.4 1.6 1.5 0.5 TNF RII 1.3 2.0 1.6 2.6 TREM-1 2.8 1.9 7.2 3.1
TROY 2.3 1.7 6.7 6.1 VEGF R1 1.9 1.3 1.8 0.3
TABLE-US-00006 TABLE 6 Summary of fold changes in the levels of
circulating factors in anti-PD1-treated vs control BALB/c and SCID
mice Fold change (anti-PD-1 vs IgG) BALB/c SCID ADAMTS1 2.4 0.3
ALK-1 3.4 3.4 Amphiregulin 3.7 0.0 CD40L 3.6 0.9 Dkk-1 2.0 0.8
Epigen 2.3 1.8 IL-17B 3.4 0.3 IL-17B R 2.1 0.9 IL-1ra 8.7 1.5 IL-21
2.6 1.0 IL-22 9.1 0.0 IL-6 2.1 1.8 I-TAC 9.3 1.1 MFG-E8 2.8 0.6
Osteoactivin 2.5 2.0 SCF 2.0 0.0 TARC 1.5 0.9 TREM-1 3.9 0.3 TROY
1.7 0.7 VEGF R1 2.6 0.8
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